Description Hybrid : 2 days per week in London, 1 day per month in Fleet Tempcover is at the forefront of the fast-growing world of short term insurance. Our mission is to make car insurance flexible, quick, and easy for drivers. We've sold millions of policies that have helped drivers get where they need to go, but we're not finished there. We're growing our team to help us continue in that mission.If you are extraordinary at what you do and want to be a part of a rapidly growing business at the cutting edge of the InsureTech industry, we would love to hear from you The Data and Analytics team within Tempcover provide a vital role in bringing data, MI and Insight to life for internal & external stakeholders and partners. The Staff Data Engineer will be responsible for the design, build and maintenance of the Tempcover cloud based data platform, supporting the wider business in making data-driven decisions. Leading the development and optimisation of data pipelines, data models and data quality controls, this role will require collaboration with data analysts and business stakeholders to translate data needs into scalable and reliable solutions. Over the past 5 years, the data platform has continually evolved through the expansion of data models, integrations and underpinning technologies. This evolution is set to continue at pace as we refine our data ingestion solutions and expand our insight capability across the business. Starting in 2026 we expect to increasingly make use of the Google Big Query platform and move away from Azure over the next 12- 18 months. What you'll be doing Design, develop, and maintain robust data pipelines and ETL processes Create and manage accurate and performant data models to support Tempcover's analytical capability. Propose and implement internal improvement initiatives to the data platform. Lead proactive approach to performance monitoring / tuning Leverage cloud-based platforms to build a scalable data infrastructure. Provide continued support to ensure high availability of data to the wider business Work closely with analysts across MI, Marketing, Product, Underwriting and Pricing to understand data requirements and translate them into effective solutions. Work with rigour to ensure data quality / accuracy. Mentor and guide junior data engineers, providing technical expertise and project oversight. What we're looking for Essential Advanced proficiency in SQL databases, including writing complex queries, indexing and query optimisation. Experience of ETL tools such as Google Cloud Dataflow, DBT, Azure Data Factory, FiveTran and Databricks. Solid understanding of data warehousing techniques; ETL / ELT processes and dimensional modelling. In-depth knowledge of cloud-based data infrastructure (GCP, Azure, AWS). Excellent problem-solving skills and the ability to work independently and collaboratively in a fast-paced environment. Proficiency with Git / DevOps for version control and collaboration. Beneficial API integration. Knowledge of Python is beneficial. Ability to work within a SCRUM agile development environment. Understanding of visualisation and dashboard products (e.g. Power BI, Tableau, Qlik) Our commitment to you At RVU, we are dedicated to developing valuable, inclusive, and user-friendly products and services that deliver positive outcomes for all of our customers. To achieve this it's essential that our teams reflect the diverse range of people in our community. We believe in being the change we wish to see in the world, by embracing our differences and holding ourselves accountable to being open and inclusive teammates and wider community members. What we offer We want to give you a great work environment, support your growth both personally and professionally, and provide benefits that make your time at RVU even more enjoyable. Here are some of the benefits you can look forward to : 10% discretionary yearly bonus and yearly pay reviews (based on RVU and personal performance) A hybrid working approach with 2 in-office days per week and up to 22 working days per year to "work from anywhere" Employer matching pension contributions up to 7.5% A one-off £300 "Work from Home" budget to help contribute towards a great work environment at home Excellent maternity, paternity, shared parental and adoption leave policy, for those key moments in your life 25 days holiday (increasing with years of employment to 30 days) + 2 days "My Time" per year Private medical cover, critical illness cover and employee assistance programme A healthy learning and training budget Electric vehicle and cycle to work schemes Regular events - from team socials to company-wide events with insightful external speakers, we want to make sure our colleagues continue to feel connected As a tech company who strives to get better every day, we use Metaview during the interview processes for note taking purposes. This records and transcribes interviews so the interviewer can fully focus on your conversation, rather than writing. This has no bearing on the assessment of you as a candidate and you can opt out at any time. Just let us know. Our culture Our culture is driven by innovation, collaboration, and a relentless focus on creating real value for our customers. With an experimentation mindset, we challenge the status quo, push boundaries, and embrace continuous learning to stay ahead. Our diverse teams are made up of brilliant people who uplift each other and work together to tackle complex problems. We work with a balance of rigour and urgency so we can learn fast and adapt to change quickly. We are a company where growth knows no limits, and where every person is empowered to make an extraordinary impact. Check out our Life At RVU page to get a further glimpse into our culture.
25/06/2026
Full time
Description Hybrid : 2 days per week in London, 1 day per month in Fleet Tempcover is at the forefront of the fast-growing world of short term insurance. Our mission is to make car insurance flexible, quick, and easy for drivers. We've sold millions of policies that have helped drivers get where they need to go, but we're not finished there. We're growing our team to help us continue in that mission.If you are extraordinary at what you do and want to be a part of a rapidly growing business at the cutting edge of the InsureTech industry, we would love to hear from you The Data and Analytics team within Tempcover provide a vital role in bringing data, MI and Insight to life for internal & external stakeholders and partners. The Staff Data Engineer will be responsible for the design, build and maintenance of the Tempcover cloud based data platform, supporting the wider business in making data-driven decisions. Leading the development and optimisation of data pipelines, data models and data quality controls, this role will require collaboration with data analysts and business stakeholders to translate data needs into scalable and reliable solutions. Over the past 5 years, the data platform has continually evolved through the expansion of data models, integrations and underpinning technologies. This evolution is set to continue at pace as we refine our data ingestion solutions and expand our insight capability across the business. Starting in 2026 we expect to increasingly make use of the Google Big Query platform and move away from Azure over the next 12- 18 months. What you'll be doing Design, develop, and maintain robust data pipelines and ETL processes Create and manage accurate and performant data models to support Tempcover's analytical capability. Propose and implement internal improvement initiatives to the data platform. Lead proactive approach to performance monitoring / tuning Leverage cloud-based platforms to build a scalable data infrastructure. Provide continued support to ensure high availability of data to the wider business Work closely with analysts across MI, Marketing, Product, Underwriting and Pricing to understand data requirements and translate them into effective solutions. Work with rigour to ensure data quality / accuracy. Mentor and guide junior data engineers, providing technical expertise and project oversight. What we're looking for Essential Advanced proficiency in SQL databases, including writing complex queries, indexing and query optimisation. Experience of ETL tools such as Google Cloud Dataflow, DBT, Azure Data Factory, FiveTran and Databricks. Solid understanding of data warehousing techniques; ETL / ELT processes and dimensional modelling. In-depth knowledge of cloud-based data infrastructure (GCP, Azure, AWS). Excellent problem-solving skills and the ability to work independently and collaboratively in a fast-paced environment. Proficiency with Git / DevOps for version control and collaboration. Beneficial API integration. Knowledge of Python is beneficial. Ability to work within a SCRUM agile development environment. Understanding of visualisation and dashboard products (e.g. Power BI, Tableau, Qlik) Our commitment to you At RVU, we are dedicated to developing valuable, inclusive, and user-friendly products and services that deliver positive outcomes for all of our customers. To achieve this it's essential that our teams reflect the diverse range of people in our community. We believe in being the change we wish to see in the world, by embracing our differences and holding ourselves accountable to being open and inclusive teammates and wider community members. What we offer We want to give you a great work environment, support your growth both personally and professionally, and provide benefits that make your time at RVU even more enjoyable. Here are some of the benefits you can look forward to : 10% discretionary yearly bonus and yearly pay reviews (based on RVU and personal performance) A hybrid working approach with 2 in-office days per week and up to 22 working days per year to "work from anywhere" Employer matching pension contributions up to 7.5% A one-off £300 "Work from Home" budget to help contribute towards a great work environment at home Excellent maternity, paternity, shared parental and adoption leave policy, for those key moments in your life 25 days holiday (increasing with years of employment to 30 days) + 2 days "My Time" per year Private medical cover, critical illness cover and employee assistance programme A healthy learning and training budget Electric vehicle and cycle to work schemes Regular events - from team socials to company-wide events with insightful external speakers, we want to make sure our colleagues continue to feel connected As a tech company who strives to get better every day, we use Metaview during the interview processes for note taking purposes. This records and transcribes interviews so the interviewer can fully focus on your conversation, rather than writing. This has no bearing on the assessment of you as a candidate and you can opt out at any time. Just let us know. Our culture Our culture is driven by innovation, collaboration, and a relentless focus on creating real value for our customers. With an experimentation mindset, we challenge the status quo, push boundaries, and embrace continuous learning to stay ahead. Our diverse teams are made up of brilliant people who uplift each other and work together to tackle complex problems. We work with a balance of rigour and urgency so we can learn fast and adapt to change quickly. We are a company where growth knows no limits, and where every person is empowered to make an extraordinary impact. Check out our Life At RVU page to get a further glimpse into our culture.
Exposure Data Analyst / Quantitative Exposure Analyst London 80,000 - 90,000 + Benefits Are you a data-driven insurance professional with strong Python and SQL skills looking to work at the forefront of exposure analytics, catastrophe risk, and process automation? I'm working with a highly regarded London Market insurer seeking an experienced Exposure Data Analyst / Quantitative Exposure Analyst to join a growing Exposure Management function. This is an excellent opportunity to combine technical expertise, data engineering, analytics and catastrophe risk management within a business where exposure analytics plays a central role in strategic decision-making. The Role Working closely with the Exposure Analytics Manager and wider Exposure Management team, you'll help develop innovative tools and analytical solutions that track, analyse and manage catastrophe exposure across the portfolio. This role offers significant exposure to modern technologies, automation initiatives, geospatial datasets, AI-driven solutions and advanced risk analytics, making it ideal for someone who enjoys solving complex problems and building scalable data solutions. Key Responsibilities Develop and enhance analytical tools used to monitor natural catastrophe exposure across the business. Build automated data pipelines and reporting processes to improve efficiency and reduce manual workloads. Support the production of portfolio analytics and catastrophe exposure forecasts. Create and maintain dashboards and visualisation tools using platforms such as Power BI and Databricks. Work with research and underwriting teams to develop proprietary risk scoring datasets and portfolio insights. Develop Python and SQL solutions that improve catastrophe pricing and exposure management processes. Translate catastrophe model outputs into business-critical reporting used for capital modelling and portfolio management. Support data enrichment initiatives and explore emerging technologies, including AI-powered solutions. Collaborate with underwriters, actuaries and senior stakeholders to deliver meaningful exposure insights. What We're Looking For Experience working within the insurance market in a data-focused analytical role. Exposure to Property insurance, catastrophe modelling or exposure management would be highly advantageous. Strong programming skills, particularly Python and SQL. Experience working with large datasets and process automation. Knowledge of catastrophe modelling platforms such as RMS or Verisk would be beneficial. Understanding of geospatial data, GIS tools or spatial analytics is desirable. Experience working with APIs, dashboarding tools and modern analytics platforms. Strong analytical and problem-solving skills with the ability to communicate complex findings clearly. A proactive, self-motivated approach and desire to improve processes through technology. Why Apply? Join a business where exposure analytics is a key strategic function. Work on innovative projects involving catastrophe risk, automation, geospatial analytics and AI. Gain exposure to senior stakeholders and underwriting teams across the organisation. Be part of a collaborative, technically strong team environment. Excellent opportunity to develop both your technical and commercial expertise within the London Market. For a confidential discussion and further information, please get in touch.
25/06/2026
Full time
Exposure Data Analyst / Quantitative Exposure Analyst London 80,000 - 90,000 + Benefits Are you a data-driven insurance professional with strong Python and SQL skills looking to work at the forefront of exposure analytics, catastrophe risk, and process automation? I'm working with a highly regarded London Market insurer seeking an experienced Exposure Data Analyst / Quantitative Exposure Analyst to join a growing Exposure Management function. This is an excellent opportunity to combine technical expertise, data engineering, analytics and catastrophe risk management within a business where exposure analytics plays a central role in strategic decision-making. The Role Working closely with the Exposure Analytics Manager and wider Exposure Management team, you'll help develop innovative tools and analytical solutions that track, analyse and manage catastrophe exposure across the portfolio. This role offers significant exposure to modern technologies, automation initiatives, geospatial datasets, AI-driven solutions and advanced risk analytics, making it ideal for someone who enjoys solving complex problems and building scalable data solutions. Key Responsibilities Develop and enhance analytical tools used to monitor natural catastrophe exposure across the business. Build automated data pipelines and reporting processes to improve efficiency and reduce manual workloads. Support the production of portfolio analytics and catastrophe exposure forecasts. Create and maintain dashboards and visualisation tools using platforms such as Power BI and Databricks. Work with research and underwriting teams to develop proprietary risk scoring datasets and portfolio insights. Develop Python and SQL solutions that improve catastrophe pricing and exposure management processes. Translate catastrophe model outputs into business-critical reporting used for capital modelling and portfolio management. Support data enrichment initiatives and explore emerging technologies, including AI-powered solutions. Collaborate with underwriters, actuaries and senior stakeholders to deliver meaningful exposure insights. What We're Looking For Experience working within the insurance market in a data-focused analytical role. Exposure to Property insurance, catastrophe modelling or exposure management would be highly advantageous. Strong programming skills, particularly Python and SQL. Experience working with large datasets and process automation. Knowledge of catastrophe modelling platforms such as RMS or Verisk would be beneficial. Understanding of geospatial data, GIS tools or spatial analytics is desirable. Experience working with APIs, dashboarding tools and modern analytics platforms. Strong analytical and problem-solving skills with the ability to communicate complex findings clearly. A proactive, self-motivated approach and desire to improve processes through technology. Why Apply? Join a business where exposure analytics is a key strategic function. Work on innovative projects involving catastrophe risk, automation, geospatial analytics and AI. Gain exposure to senior stakeholders and underwriting teams across the organisation. Be part of a collaborative, technically strong team environment. Excellent opportunity to develop both your technical and commercial expertise within the London Market. For a confidential discussion and further information, please get in touch.
Data Architect Hybrid RCT (South Wales) IntaPeople are proud and excited to be appointed to recruit an experienced Data Architect for a Welsh-based not-for-profit sector client during a rapid growth spurt. This is a very exciting opportunity to join their fast-growing Data function in this newly created position. You will be joining the data team as one of the first handful of team members in this area of the business which will work with external partners to build out the organisations data capability offering. As a Data Architect, you will be responsible for designing, building, and maintaining robust, scalable, and secure data pipelines and platform that enable them to make data-driven decisions at a enterprise level. Working closely with the 'Head of Data Engineering' you will help grow out this data function with the recruitment of further data engineering resources whilst working closely with solutions architects and Software Engineers. You will also get the opportunity to progress into a leadership role if this suited the individuals' desires and capabilities. You will shape, govern and assure the organisation's data architecture, defining, designing and maintaining strategic data models, standards, flows and governance structures that support organisational goals, ensure compliance, foster collaboration across business areas, and enable the organisation to make data-driven decisions Essential Skills Proven experience as a Senior Data Engineer or Data Architect (or similar/related role). Experience with Enterprise level Data sets. Expertise and practical experience in designing and aligning data models across multiple subject areas, applying recognised patterns and industry standards. Familiarity with structured architectural approaches found in TOGAF (data architecture) or equivalent. Proven experience defining and evolving data governance, including data quality, metadata, lineage, and policy assurance across services. Strong capability in data profiling, source system analysis and identifying links across problem domains to define common, reusable solutions. Experience of communicating technical information and data to a non technical audience and working collaboratively with analysts, architects, and product owners to deliver data solutions that meet user and organisational needs. Ability to lead and mentor other team members. Demonstrable knowledge of data modelling and data warehousing within platforms such as Azure or AWS. Practical experience with Microsoft Azure services, including Azure Data Lake (Gen2), Synapse, Event Hubs, and Cosmos DB, within scalable cloud based architectures. Robust understanding of data governance, data quality, and metadata management. Desirable skills Experience with Azure Data Factory, Databricks, or Apache Spark, following modern ETL/ELT principles. Experience in using Git, Azure DevOps, or GitHub Actions for version control, CI/CD, and collaborative data delivery. Experience with Big Data. Certification in data architecture or governance frameworks (e.g., TOGAF, DAMA, DCAM, EDMC). Experience of using programming languages such as Python, Scala and SQL. Welsh language skills. Key Responsibilities (at a glance) Establish Data strategies and data modelling internally within the data estate. Lead the design and oversight of enterprise aligned data models and supporting data architecture, ensuring that all modelling approaches follow organisational standards, recognised patterns, and enable scalable, high quality data flows across services. Provide expert architectural guidance to technical teams delivering cloud based data platforms, ensuring that data integration, modelling, metadata and design decisions align with organisational and enterprise wide standards. Work closely with other business leaders to maintain governance and compliance within their data estate. Work closely with data analysts, data engineering, Enterprise and solution architects, DevOps, and business stakeholders through regular communication and collaborative planning to ensure data solutions are closely aligned with business objectives and effectively meet user needs. Contribute to the development and execution of the Data Strategy by maintaining thorough documentation of data processes, architectures, and workflows to ensure all technical and process information is systematically recorded, updated and data initiatives deliver business value and are aligned with broader technology and organisational goals. Research into emerging technologies and upcoming trends. Provide oversight to teams building data processing pipelines and integration patterns, ensuring their artefacts are consistent with data architecture principles and metadata strategies. Lead on the introduction of foundational data management capabilities to improve trust, accessibility, and efficiency in an organisation that has limited data management capability, lacks data management practices, including governance, metadata standards, and quality controls. Design, implement, and optimise physical data models that align with pipeline architecture, by using the approach that ensures efficient query performance, scalable storage, and robust integration and delivers adaptable and resource efficient data processing, meeting the organisation's evolving analytical and operational demands. Managing the aspirations of a variety of stakeholders to enable successful project delivery can be challenging, especially when their priorities may differ or even conflict and require reconciliation to meet business and project needs. What you'll get in return (at a glance) A salary of circa £64,000 - £65,000 (depending on experience) 28 days annual leave + public bank holidays Hybrid working - to be based in their brand new, modern offices 1 2 days per week A flexible working environment Competitive Legal and General pension Scheme (8% employer contribution) 4 death in service The opportunity to work on modern and industry changing projects Progression and development opportunities Free Rail travel throughout Wales and discounted throughout the UK Salary sacrifice scheme such as cycle to work, electric vehicle A chance to truly contribute to large scale digitalisation projects within Wales This role is commutable from Swansea, Bridgend, Pontypridd, Cardiff and Newport or surrounding areas.
24/06/2026
Full time
Data Architect Hybrid RCT (South Wales) IntaPeople are proud and excited to be appointed to recruit an experienced Data Architect for a Welsh-based not-for-profit sector client during a rapid growth spurt. This is a very exciting opportunity to join their fast-growing Data function in this newly created position. You will be joining the data team as one of the first handful of team members in this area of the business which will work with external partners to build out the organisations data capability offering. As a Data Architect, you will be responsible for designing, building, and maintaining robust, scalable, and secure data pipelines and platform that enable them to make data-driven decisions at a enterprise level. Working closely with the 'Head of Data Engineering' you will help grow out this data function with the recruitment of further data engineering resources whilst working closely with solutions architects and Software Engineers. You will also get the opportunity to progress into a leadership role if this suited the individuals' desires and capabilities. You will shape, govern and assure the organisation's data architecture, defining, designing and maintaining strategic data models, standards, flows and governance structures that support organisational goals, ensure compliance, foster collaboration across business areas, and enable the organisation to make data-driven decisions Essential Skills Proven experience as a Senior Data Engineer or Data Architect (or similar/related role). Experience with Enterprise level Data sets. Expertise and practical experience in designing and aligning data models across multiple subject areas, applying recognised patterns and industry standards. Familiarity with structured architectural approaches found in TOGAF (data architecture) or equivalent. Proven experience defining and evolving data governance, including data quality, metadata, lineage, and policy assurance across services. Strong capability in data profiling, source system analysis and identifying links across problem domains to define common, reusable solutions. Experience of communicating technical information and data to a non technical audience and working collaboratively with analysts, architects, and product owners to deliver data solutions that meet user and organisational needs. Ability to lead and mentor other team members. Demonstrable knowledge of data modelling and data warehousing within platforms such as Azure or AWS. Practical experience with Microsoft Azure services, including Azure Data Lake (Gen2), Synapse, Event Hubs, and Cosmos DB, within scalable cloud based architectures. Robust understanding of data governance, data quality, and metadata management. Desirable skills Experience with Azure Data Factory, Databricks, or Apache Spark, following modern ETL/ELT principles. Experience in using Git, Azure DevOps, or GitHub Actions for version control, CI/CD, and collaborative data delivery. Experience with Big Data. Certification in data architecture or governance frameworks (e.g., TOGAF, DAMA, DCAM, EDMC). Experience of using programming languages such as Python, Scala and SQL. Welsh language skills. Key Responsibilities (at a glance) Establish Data strategies and data modelling internally within the data estate. Lead the design and oversight of enterprise aligned data models and supporting data architecture, ensuring that all modelling approaches follow organisational standards, recognised patterns, and enable scalable, high quality data flows across services. Provide expert architectural guidance to technical teams delivering cloud based data platforms, ensuring that data integration, modelling, metadata and design decisions align with organisational and enterprise wide standards. Work closely with other business leaders to maintain governance and compliance within their data estate. Work closely with data analysts, data engineering, Enterprise and solution architects, DevOps, and business stakeholders through regular communication and collaborative planning to ensure data solutions are closely aligned with business objectives and effectively meet user needs. Contribute to the development and execution of the Data Strategy by maintaining thorough documentation of data processes, architectures, and workflows to ensure all technical and process information is systematically recorded, updated and data initiatives deliver business value and are aligned with broader technology and organisational goals. Research into emerging technologies and upcoming trends. Provide oversight to teams building data processing pipelines and integration patterns, ensuring their artefacts are consistent with data architecture principles and metadata strategies. Lead on the introduction of foundational data management capabilities to improve trust, accessibility, and efficiency in an organisation that has limited data management capability, lacks data management practices, including governance, metadata standards, and quality controls. Design, implement, and optimise physical data models that align with pipeline architecture, by using the approach that ensures efficient query performance, scalable storage, and robust integration and delivers adaptable and resource efficient data processing, meeting the organisation's evolving analytical and operational demands. Managing the aspirations of a variety of stakeholders to enable successful project delivery can be challenging, especially when their priorities may differ or even conflict and require reconciliation to meet business and project needs. What you'll get in return (at a glance) A salary of circa £64,000 - £65,000 (depending on experience) 28 days annual leave + public bank holidays Hybrid working - to be based in their brand new, modern offices 1 2 days per week A flexible working environment Competitive Legal and General pension Scheme (8% employer contribution) 4 death in service The opportunity to work on modern and industry changing projects Progression and development opportunities Free Rail travel throughout Wales and discounted throughout the UK Salary sacrifice scheme such as cycle to work, electric vehicle A chance to truly contribute to large scale digitalisation projects within Wales This role is commutable from Swansea, Bridgend, Pontypridd, Cardiff and Newport or surrounding areas.
Job title: Data Analyst Locations: Manchester (hybrid working) Role overview As a Data Analyst at Markerstudy, you will contribute to the delivery of analytics solutions that support strategic decision-making across our insurance brands. Working within the Analytics & Enrichment team, you'll help generate insights that improve insurer panel performance collaborating with teams across pricing and insurer relations. This role is ideal for someone with a strong analytical foundation, a passion for data, and a desire to grow their technical and commercial skills in a fast-paced, data-driven environment. Markerstudy is a leading provider of private insurance in the UK, insuring around 5% of the private cars on the UK roads, 20% of commercial vehicles and over 30% of motorcycles in total premium levels of circa £1b. Most of Markerstudy's business is written as the insurance pricing provider behind household names such as Tesco, Sainsbury's, O2, Halifax, AA, Saga and Lloyds Bank to list a few. Key Responsibilities: Deliver high-quality analysis: Produce accurate, timely insights that support day-to-day business decisions. Answer business questions with data: Analyse datasets to explain performance, identify trends, and highlight opportunities or risks. Collaborate with stakeholders: Work with partners to understand requirements, clarify questions, and respond to feedback. Maintain reporting and dashboards: Build, refresh, and monitor reports tracking key metrics and KPIs. Support analytical models and processes: Contribute to the development, testing, and ongoing monitoring of existing models such as marketing selection models. Continuously develop analytical skills: Build technical and business knowledge, staying curious and open to new tools and techniques. Key Skills and Experience: Strong academic background in a numerical discipline (eg BSc Mathematics, Computer Science, Data Science). Proficiency in SQL and working knowledge of Python and/or R. Understanding of statistical and machine learning techniques (e.g. regression, clustering). Strong communication skills with the ability to explain technical concepts to non-technical audiences. Organised, proactive, and able to manage multiple tasks effectively. Desirable Postgraduate qualification in relevant field (eg Computer Science, Data Science, Operational Research) Experience with modern data platforms (eg Databricks, Snowflake, MS Fabric). Familiarity with MLOps practices and version control tools (e.g. Git). Experience with deployment and maintenance of ML models in production environments. SQL MS Excel Power BI Python and/or R Behaviours: Collaborative and team player Logical thinker with a professional and positive attitude Passion to innovate and improve processes
24/06/2026
Full time
Job title: Data Analyst Locations: Manchester (hybrid working) Role overview As a Data Analyst at Markerstudy, you will contribute to the delivery of analytics solutions that support strategic decision-making across our insurance brands. Working within the Analytics & Enrichment team, you'll help generate insights that improve insurer panel performance collaborating with teams across pricing and insurer relations. This role is ideal for someone with a strong analytical foundation, a passion for data, and a desire to grow their technical and commercial skills in a fast-paced, data-driven environment. Markerstudy is a leading provider of private insurance in the UK, insuring around 5% of the private cars on the UK roads, 20% of commercial vehicles and over 30% of motorcycles in total premium levels of circa £1b. Most of Markerstudy's business is written as the insurance pricing provider behind household names such as Tesco, Sainsbury's, O2, Halifax, AA, Saga and Lloyds Bank to list a few. Key Responsibilities: Deliver high-quality analysis: Produce accurate, timely insights that support day-to-day business decisions. Answer business questions with data: Analyse datasets to explain performance, identify trends, and highlight opportunities or risks. Collaborate with stakeholders: Work with partners to understand requirements, clarify questions, and respond to feedback. Maintain reporting and dashboards: Build, refresh, and monitor reports tracking key metrics and KPIs. Support analytical models and processes: Contribute to the development, testing, and ongoing monitoring of existing models such as marketing selection models. Continuously develop analytical skills: Build technical and business knowledge, staying curious and open to new tools and techniques. Key Skills and Experience: Strong academic background in a numerical discipline (eg BSc Mathematics, Computer Science, Data Science). Proficiency in SQL and working knowledge of Python and/or R. Understanding of statistical and machine learning techniques (e.g. regression, clustering). Strong communication skills with the ability to explain technical concepts to non-technical audiences. Organised, proactive, and able to manage multiple tasks effectively. Desirable Postgraduate qualification in relevant field (eg Computer Science, Data Science, Operational Research) Experience with modern data platforms (eg Databricks, Snowflake, MS Fabric). Familiarity with MLOps practices and version control tools (e.g. Git). Experience with deployment and maintenance of ML models in production environments. SQL MS Excel Power BI Python and/or R Behaviours: Collaborative and team player Logical thinker with a professional and positive attitude Passion to innovate and improve processes
Data Engineer Department: IT & Change Employment Type: Permanent - Full Time Location: Manchester, UK Description We are seeking highly skilled and experienced Azure Data Engineers to join a newly formed group concentrating on Data. Within this role you will be a key member of the team, working on a complex and challenging project within the Financial Services/Capital Markets industry. The primary focus of the role would be on building resilient, reusable Data Pipelines to extract, load, and transform raw data into a relational data model. The successful candidate will work across complex, multi-source datasets including loan servicing systems, property and valuation platforms, collections systems, and third-party data providers, delivering reliable and auditable data at scale. Key Responsibilities Serve as the team's ADF, Databricks, Python, PySpark & Spark SQL technical expert Responsible for day-to-day collection & ingestion of raw data into corporate data assets Work with the team to formalize data flows and data standards Enable trusted datasets for portfolio analytics, asset strategy, finance, and risk Supervise all data ingestion & integration processes from source to target including the data warehouse, data lake, etc Performance tune and optimize all data ingestion and data integration processes Partner with Data Stewards and Business Analysts to understand the nature of the data being handled and what an optimal Data Pipeline for it should look like Design solutions that are aligned to the target state Data Architecture About you Degree in Computer Science, Information Systems, Data Science, or a related field is preferable Proven experience building resilient, reusable Data Pipelines as a Data Engineer or equivalent Resourceful, motivated self-starter with the ability to collaborate across business and technology Strong analytical, verbal, and written communication skills A background in financial data domains (IBOR/ABOR, transactions, market data, reference data) Strong experience as a Data Engineer within Real Estate, Credit, Banking, or NPL Asset Management Microsoft certification a plus
24/06/2026
Full time
Data Engineer Department: IT & Change Employment Type: Permanent - Full Time Location: Manchester, UK Description We are seeking highly skilled and experienced Azure Data Engineers to join a newly formed group concentrating on Data. Within this role you will be a key member of the team, working on a complex and challenging project within the Financial Services/Capital Markets industry. The primary focus of the role would be on building resilient, reusable Data Pipelines to extract, load, and transform raw data into a relational data model. The successful candidate will work across complex, multi-source datasets including loan servicing systems, property and valuation platforms, collections systems, and third-party data providers, delivering reliable and auditable data at scale. Key Responsibilities Serve as the team's ADF, Databricks, Python, PySpark & Spark SQL technical expert Responsible for day-to-day collection & ingestion of raw data into corporate data assets Work with the team to formalize data flows and data standards Enable trusted datasets for portfolio analytics, asset strategy, finance, and risk Supervise all data ingestion & integration processes from source to target including the data warehouse, data lake, etc Performance tune and optimize all data ingestion and data integration processes Partner with Data Stewards and Business Analysts to understand the nature of the data being handled and what an optimal Data Pipeline for it should look like Design solutions that are aligned to the target state Data Architecture About you Degree in Computer Science, Information Systems, Data Science, or a related field is preferable Proven experience building resilient, reusable Data Pipelines as a Data Engineer or equivalent Resourceful, motivated self-starter with the ability to collaborate across business and technology Strong analytical, verbal, and written communication skills A background in financial data domains (IBOR/ABOR, transactions, market data, reference data) Strong experience as a Data Engineer within Real Estate, Credit, Banking, or NPL Asset Management Microsoft certification a plus
Role: Data Engineer Location: Newcastle Upon Tyne Salary: TBC - Depending on experience Levels: Senior Analyst, Specialist Hybrid Working: 3 days per week in our Newcastle, Cobalt business park office Please Note: Any offer of employment is subject to satisfactory BPSS and SC security clearance which requires 5 years continuous UK address history (typically including no periods of 30 consecutive days or more spent outside of the UK) and declaration of being a British or EU passport holder or hold Indefinite Leave to remain within the UK at the point of application. Note: The above information relates to a specific client requirement About the Team Our Advanced Technology Centre is a hub of innovation where we deliver high quality data and technology services to clients across both the public and private sectors. If you're looking for a dynamic role that offers hands on experience with modern data technologies and the chance to shape large scale data solutions, this position offers you the opportunity to develop and progress rapidly. Role Overview As a Data Engineer, you will design, build, and maintain scalable data solutions that enable analytics, AI, and operational insights. You'll work alongside client and internal teams to create robust data pipelines, ensure data reliability, and support cloud based architectures that power intelligent decision making. Key Responsibilities Data Pipeline Development Build, optimize, and maintain scalable data pipelines using Java (primary), plus exposure to Python, Flink, Kafka, or Spark. Develop and support real time streaming pipelines and event driven integrations. Integrate data from multiple sources (streaming, batch, APIs) using AWS managed services (e.g., Kinesis, MSK, Lambda, Glue). Data Architecture & Standards Contribute to data modelling, data architecture best practices, and modern patterns (e.g., medallion architecture). Ensure data quality, lineage, governance, and security controls are applied consistently. DevOps & Deployment Deploy and maintain data applications using CI/CD tooling (Azure DevOps, GitHub Actions, Jenkins). Use Infrastructure as Code (Terraform, CloudFormation) to manage cloud environments. Work with container technologies such as Docker and Kubernetes based workloads. Collaboration Work closely with analytics, ML/AI, and product teams to deliver clean, well structured datasets. Participate in code reviews and internal knowledge sharing sessions. Provide guidance to junior engineers where needed. Qualification Core Data Engineering Strong programming proficiency in Java (preferred) or Python. Hands on experience with at least one of: Kafka, Flink, Spark (Flink/Kafka preferred for streaming). Solid understanding of stream processing concepts (e.g., event time, state, backpressure). Understanding of software engineering best practices: testing, design patterns, CI/CD, Git. Experience building ETL/ELT or streaming data pipelines. Exposure to microservices and distributed system concepts. Experience working with cloud platforms, ideally AWS, but Azure/GCP also acceptable. Understanding of distributed compute, large scale data systems, and performance considerations. DevOps & Engineering Practices Experience with CI/CD tools (Azure DevOps, GitHub Actions, Jenkins etc.). Infrastructure as Code (Terraform preferred). Experience with containerisation (Docker) and orchestration platforms (Kubernetes/EKS). Certifications & Tools Exposure to enterprise data platforms (Databricks, Snowflake, BigQuery, or similar). Cloud certifications (AWS, Azure, GCP) are beneficial but not required. Other Requirements Minimum 3 years' experience working on data engineering or large scale data solutions. Comfortable working in Agile delivery teams. Strong communication skills and ability to collaborate with technical and non technical stakeholders. Desirable Experience in client facing or consulting environments. Professional cloud or data engineering certifications. Experience mentoring or supporting junior engineers. Background in designing or operating real time, low latency systems.
24/06/2026
Full time
Role: Data Engineer Location: Newcastle Upon Tyne Salary: TBC - Depending on experience Levels: Senior Analyst, Specialist Hybrid Working: 3 days per week in our Newcastle, Cobalt business park office Please Note: Any offer of employment is subject to satisfactory BPSS and SC security clearance which requires 5 years continuous UK address history (typically including no periods of 30 consecutive days or more spent outside of the UK) and declaration of being a British or EU passport holder or hold Indefinite Leave to remain within the UK at the point of application. Note: The above information relates to a specific client requirement About the Team Our Advanced Technology Centre is a hub of innovation where we deliver high quality data and technology services to clients across both the public and private sectors. If you're looking for a dynamic role that offers hands on experience with modern data technologies and the chance to shape large scale data solutions, this position offers you the opportunity to develop and progress rapidly. Role Overview As a Data Engineer, you will design, build, and maintain scalable data solutions that enable analytics, AI, and operational insights. You'll work alongside client and internal teams to create robust data pipelines, ensure data reliability, and support cloud based architectures that power intelligent decision making. Key Responsibilities Data Pipeline Development Build, optimize, and maintain scalable data pipelines using Java (primary), plus exposure to Python, Flink, Kafka, or Spark. Develop and support real time streaming pipelines and event driven integrations. Integrate data from multiple sources (streaming, batch, APIs) using AWS managed services (e.g., Kinesis, MSK, Lambda, Glue). Data Architecture & Standards Contribute to data modelling, data architecture best practices, and modern patterns (e.g., medallion architecture). Ensure data quality, lineage, governance, and security controls are applied consistently. DevOps & Deployment Deploy and maintain data applications using CI/CD tooling (Azure DevOps, GitHub Actions, Jenkins). Use Infrastructure as Code (Terraform, CloudFormation) to manage cloud environments. Work with container technologies such as Docker and Kubernetes based workloads. Collaboration Work closely with analytics, ML/AI, and product teams to deliver clean, well structured datasets. Participate in code reviews and internal knowledge sharing sessions. Provide guidance to junior engineers where needed. Qualification Core Data Engineering Strong programming proficiency in Java (preferred) or Python. Hands on experience with at least one of: Kafka, Flink, Spark (Flink/Kafka preferred for streaming). Solid understanding of stream processing concepts (e.g., event time, state, backpressure). Understanding of software engineering best practices: testing, design patterns, CI/CD, Git. Experience building ETL/ELT or streaming data pipelines. Exposure to microservices and distributed system concepts. Experience working with cloud platforms, ideally AWS, but Azure/GCP also acceptable. Understanding of distributed compute, large scale data systems, and performance considerations. DevOps & Engineering Practices Experience with CI/CD tools (Azure DevOps, GitHub Actions, Jenkins etc.). Infrastructure as Code (Terraform preferred). Experience with containerisation (Docker) and orchestration platforms (Kubernetes/EKS). Certifications & Tools Exposure to enterprise data platforms (Databricks, Snowflake, BigQuery, or similar). Cloud certifications (AWS, Azure, GCP) are beneficial but not required. Other Requirements Minimum 3 years' experience working on data engineering or large scale data solutions. Comfortable working in Agile delivery teams. Strong communication skills and ability to collaborate with technical and non technical stakeholders. Desirable Experience in client facing or consulting environments. Professional cloud or data engineering certifications. Experience mentoring or supporting junior engineers. Background in designing or operating real time, low latency systems.
Compare The Market Limited
Peterborough, Cambridgeshire
Analytics Engineer Function: Data Location: Hybrid, London or Peterborough office We'dlove you to be part of our journey: We'relooking for an Analytics Engineer who wants to grow their individual contributor career by solving complex data problems and contributing to the foundations of a modern, self-serve analytics platform. This role is ideal for someone who enjoys working collaboratively, building reusable and scalable data models, and making data more accessible across the business. You will also take on cross-domain technical ownership and contribute to technical strategy and standards across the organisation. Some of thegreat thingsyou'lldo: Develop andmaintainscalableDBTmodels, transformation pipelines, and analytics workflows. Build and support BI reporting and dashboards using modernvisualisationtools. Partner with analysts, product teams, and engineers to understand business requirements and translate them into robust data solutions. Contribute to the design andoptimisationof analytics-ready data models with a focus on usability, performance, and maintainability. Implement andmaintaindata quality checks, testing, and documentation to improve trust in analytics outputs. Support operational excellence across the analytics stack through automation, monitoring, and continuous improvement. Participate in code reviews, knowledge sharing, and team-wide engineering practices. Contribute to analytics engineering standards, documentation, and best practices. Support platform initiatives including migrations, model refactoring, governance improvements, and technical debt reduction. Collaborate effectively across technical and non-technical teams to deliver high-quality outcomes. Whatwe'dlike to see from you: Strong SQL skills and experience working with DBTor similar transformation frameworks. Experience building analytics-ready data models and reporting solutions. Understanding ofdata modelling principles, testing, and queryoptimisation. Familiarity with modern engineering practices such as Git, CI/CD, and automated testing. Strong problem-solving skills and attention to detail. Ability to communicate effectively with both technical and business stakeholders. A collaborative mindset and willingness to learn and grow in a fast-moving environment. Nice to have: Experience with Databricks, Spark, or Airflow. Exposure tocloud data platforms and modern data architectures. Experience supporting data platform migrations ormodernisationinitiatives. Familiarity with observability, monitoring, or data reliabilitypractices. Job Info Job Identification 100234 Job Category Technology Posting Date 05/21/2026, 03:22 PM Job Schedule Full time Locations White Collar Factory, London, London, EC1Y 8AF, GB Pegasus House, Peterborough, Cambridgeshire, PE2 6YS, GB (Hybrid)
24/06/2026
Full time
Analytics Engineer Function: Data Location: Hybrid, London or Peterborough office We'dlove you to be part of our journey: We'relooking for an Analytics Engineer who wants to grow their individual contributor career by solving complex data problems and contributing to the foundations of a modern, self-serve analytics platform. This role is ideal for someone who enjoys working collaboratively, building reusable and scalable data models, and making data more accessible across the business. You will also take on cross-domain technical ownership and contribute to technical strategy and standards across the organisation. Some of thegreat thingsyou'lldo: Develop andmaintainscalableDBTmodels, transformation pipelines, and analytics workflows. Build and support BI reporting and dashboards using modernvisualisationtools. Partner with analysts, product teams, and engineers to understand business requirements and translate them into robust data solutions. Contribute to the design andoptimisationof analytics-ready data models with a focus on usability, performance, and maintainability. Implement andmaintaindata quality checks, testing, and documentation to improve trust in analytics outputs. Support operational excellence across the analytics stack through automation, monitoring, and continuous improvement. Participate in code reviews, knowledge sharing, and team-wide engineering practices. Contribute to analytics engineering standards, documentation, and best practices. Support platform initiatives including migrations, model refactoring, governance improvements, and technical debt reduction. Collaborate effectively across technical and non-technical teams to deliver high-quality outcomes. Whatwe'dlike to see from you: Strong SQL skills and experience working with DBTor similar transformation frameworks. Experience building analytics-ready data models and reporting solutions. Understanding ofdata modelling principles, testing, and queryoptimisation. Familiarity with modern engineering practices such as Git, CI/CD, and automated testing. Strong problem-solving skills and attention to detail. Ability to communicate effectively with both technical and business stakeholders. A collaborative mindset and willingness to learn and grow in a fast-moving environment. Nice to have: Experience with Databricks, Spark, or Airflow. Exposure tocloud data platforms and modern data architectures. Experience supporting data platform migrations ormodernisationinitiatives. Familiarity with observability, monitoring, or data reliabilitypractices. Job Info Job Identification 100234 Job Category Technology Posting Date 05/21/2026, 03:22 PM Job Schedule Full time Locations White Collar Factory, London, London, EC1Y 8AF, GB Pegasus House, Peterborough, Cambridgeshire, PE2 6YS, GB (Hybrid)
About UBDS UBDS Group empowers organizations to achieve remarkable digital transformations through innovative technology solutions. We work with clients across the public and private sector to design and build products, platforms and services that genuinely make a difference to users. We're looking for a Senior Data Engineer who combines deep technical capability with a strong consulting mindset. Someone who enjoys ambiguity, cares about users, and can turn messy business problems into robust, production-grade data solutions. The Role As a Senior Data Engineer at UBDS, you'll work closely with clients, designers, analysts and engineers to shape and deliver modern data solutions end to end. You'll be trusted to lead technical thinking, make pragmatic design decisions, and support teams in delivering high quality outcomes that stand up in the real world. This is a hands on role with influence: you'll be building, guiding others, and helping clients understand what good looks like. What You'll Do Turn ambiguous business problems into clear data, analytical and technical solutions. Design, build and operate production grade data pipelines, models and products using SQL, Python and modern data engineering frameworks. Architect and work across data warehouses, lakehouse and event driven patterns, including strong semantic models for analytics and visualisation. Deliver solutions on cloud data and AI platforms (AWS/Azure), applying solid software engineering, testing and CI/CD practices. Embed analytics, experimentation, AI/ML integration, governance, security and data quality best practices by default. Create clear data visualisations, narratives and consultant grade materials that help clients understand and act on insight. Work closely with users and stakeholders in Agile, client driven environments, learning from live services and real world feedback. Apply strong critical thinking, attention to detail and relevant industry and government standards to deliver solutions that are easy to hand over, maintain and evolve. What We're Looking For Core Data & Technical Skills Ability to translate ambiguous business problems into clear data, analytical and technical requirements. Strong SQL and Python skills for data modelling, transformation, automation and analysis. Experience designing data models and architectures across data warehouses, lakehouse and event driven patterns, or strong semantic modelling in Power BI or other visualisation tools. Hands on experience with modern data engineering frameworks such as Spark / PySpark, Pandas and orchestration tools. Experience working with cloud data and AI platforms on AWS or Azure (e.g. Databricks, Redshift, Bedrock, Microsoft Fabric). Solid software engineering fundamentals, including Git, testing and QA, CI/CD pipelines and modular, maintainable design. Strong analytics and statistical reasoning, including metric design, experimentation and interpretation of results. Practical AI/ML literacy, including integrating model APIs, evaluation approaches and prompt orchestration. Experience applying data governance, security and quality best practices, such as access control, data catalogues, lineage and GDPR awareness. Ability to communicate insight through data visualisation and storytelling using tools like Power BI, Tableau or Python based charts. Consulting & Delivery Mindset A user centred approach: curiosity about who will use the solution, why it matters, and the impact it will have. Confidence communicating clearly and working effectively in ambiguous, client driven environments. Ability to produce high quality, consultant grade slides and written materials. Strong critical thinking, with a clear and logical approach to defining and delivering data solutions. Proven experience delivering production grade solutions to real users, supporting live services and learning from real world feedback. High attention to detail, including readable code, consistent naming conventions and clear technical and user documentation. A product driven mindset, with experience delivering features and outcomes iteratively in Agile teams. Familiarity with relevant industry and government standards, and a habit of seeking out appropriate standards at the start of delivery rather than reinventing solutions. Employee Benefits Training - All team members are offered a number of options in terms of personal development, whether it is technical led, business acumen or methodologies. We want you to grow with us and to help us achieve more. Private medical cover for you and your spouse/partner, offered via Vitality. Discretionary bonus based on a blend of personal and company performance. Holiday - You will receive 25 Days holiday, plus 1 day for Birthday and 1 day for your work anniversary in addition to UK bank holidays. Electric Vehicle leasing with salary sacrifice. Contributed Pension Scheme. Death in service cover. Equal Opportunities We are an equal opportunities employer and do not discriminate on the grounds of gender, sexual orientation, marital or civil partner status, pregnancy or maternity, gender reassignment, race, colour, nationality, ethnic or national origin, religion or belief, disability or age.
23/06/2026
Full time
About UBDS UBDS Group empowers organizations to achieve remarkable digital transformations through innovative technology solutions. We work with clients across the public and private sector to design and build products, platforms and services that genuinely make a difference to users. We're looking for a Senior Data Engineer who combines deep technical capability with a strong consulting mindset. Someone who enjoys ambiguity, cares about users, and can turn messy business problems into robust, production-grade data solutions. The Role As a Senior Data Engineer at UBDS, you'll work closely with clients, designers, analysts and engineers to shape and deliver modern data solutions end to end. You'll be trusted to lead technical thinking, make pragmatic design decisions, and support teams in delivering high quality outcomes that stand up in the real world. This is a hands on role with influence: you'll be building, guiding others, and helping clients understand what good looks like. What You'll Do Turn ambiguous business problems into clear data, analytical and technical solutions. Design, build and operate production grade data pipelines, models and products using SQL, Python and modern data engineering frameworks. Architect and work across data warehouses, lakehouse and event driven patterns, including strong semantic models for analytics and visualisation. Deliver solutions on cloud data and AI platforms (AWS/Azure), applying solid software engineering, testing and CI/CD practices. Embed analytics, experimentation, AI/ML integration, governance, security and data quality best practices by default. Create clear data visualisations, narratives and consultant grade materials that help clients understand and act on insight. Work closely with users and stakeholders in Agile, client driven environments, learning from live services and real world feedback. Apply strong critical thinking, attention to detail and relevant industry and government standards to deliver solutions that are easy to hand over, maintain and evolve. What We're Looking For Core Data & Technical Skills Ability to translate ambiguous business problems into clear data, analytical and technical requirements. Strong SQL and Python skills for data modelling, transformation, automation and analysis. Experience designing data models and architectures across data warehouses, lakehouse and event driven patterns, or strong semantic modelling in Power BI or other visualisation tools. Hands on experience with modern data engineering frameworks such as Spark / PySpark, Pandas and orchestration tools. Experience working with cloud data and AI platforms on AWS or Azure (e.g. Databricks, Redshift, Bedrock, Microsoft Fabric). Solid software engineering fundamentals, including Git, testing and QA, CI/CD pipelines and modular, maintainable design. Strong analytics and statistical reasoning, including metric design, experimentation and interpretation of results. Practical AI/ML literacy, including integrating model APIs, evaluation approaches and prompt orchestration. Experience applying data governance, security and quality best practices, such as access control, data catalogues, lineage and GDPR awareness. Ability to communicate insight through data visualisation and storytelling using tools like Power BI, Tableau or Python based charts. Consulting & Delivery Mindset A user centred approach: curiosity about who will use the solution, why it matters, and the impact it will have. Confidence communicating clearly and working effectively in ambiguous, client driven environments. Ability to produce high quality, consultant grade slides and written materials. Strong critical thinking, with a clear and logical approach to defining and delivering data solutions. Proven experience delivering production grade solutions to real users, supporting live services and learning from real world feedback. High attention to detail, including readable code, consistent naming conventions and clear technical and user documentation. A product driven mindset, with experience delivering features and outcomes iteratively in Agile teams. Familiarity with relevant industry and government standards, and a habit of seeking out appropriate standards at the start of delivery rather than reinventing solutions. Employee Benefits Training - All team members are offered a number of options in terms of personal development, whether it is technical led, business acumen or methodologies. We want you to grow with us and to help us achieve more. Private medical cover for you and your spouse/partner, offered via Vitality. Discretionary bonus based on a blend of personal and company performance. Holiday - You will receive 25 Days holiday, plus 1 day for Birthday and 1 day for your work anniversary in addition to UK bank holidays. Electric Vehicle leasing with salary sacrifice. Contributed Pension Scheme. Death in service cover. Equal Opportunities We are an equal opportunities employer and do not discriminate on the grounds of gender, sexual orientation, marital or civil partner status, pregnancy or maternity, gender reassignment, race, colour, nationality, ethnic or national origin, religion or belief, disability or age.
We don't just believe in better. We make it happen. Better content. Better products. And better careers. Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, Sky Stream to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. Role overview Our products, platforms and technologies are constantly evolving that's why keeping Sky safe from cyber-attacks is one of our top priorities. Our Cyber Security team helps the business grow while protecting our customers, colleagues and partners from increasingly sophisticated cyber threats. Our team includes Cyber Fusion Centre, Security Services, Risk and Compliance, Programme Delivery and Business Security, and we work across the UK, Italy and Germany. Join us and you'll get involved in tackling challenges and future threats in an ever-changing cyber landscape. You will join our comprehensive Cyber Defence Department as a senior member of the dedicated Threat Hunt team. You will operate within a robust security ecosystem, partnering directly with Cyber Operations, Threat Intelligence, Engineering, and Threat Vulnerability Management. What you'll do : Conduct proactive threat hunts across the enterprise, broadcast, and telco networks to identify abnormal activity, emerging attack techniques, and advanced threats. Develop and execute hypothesis-driven threat hunts utilising datasets across a variety of security tooling, including EDR, SIEM, and network-layer defences. Collaborate directly with the Cyber Threat Intelligence team to operationalise intelligence, maintaining and refining hunting playbooks for priority threat actors and relevant TTPs. Partner with security engineering teams to translate hunt findings into productionised, high-fidelity detections and drive continuous improvement in data source coverage and quality. Act as a technical mentor within the Cyber Defence function, guiding junior analysts, conducting peer reviews, and fostering a culture of continuous learning. Document and communicate hunt outcomes comprehensively, translating complex technical findings into actionable remediation strategies and executive-level summaries. What you'll bring : Essential Criteria Extensive prior experience in threat hunting at a large enterprise environment. Experience with incident response, SOC, or detection engineering. Deep understanding of the MITRE ATT&CK framework and how to practically apply it to threat hunting methodologies and detection logic. Proficiency in complex query writing (e.g., KQL, SPL, SQL) to filter, analyse, and visualise large, disparate datasets. Hands-on experience with EDR, NDR, SIEM, SOAR security platforms and data analysis platforms such as Databricks. Strong investigative acumen combined with a curious, highly analytical mindset capable of navigating ambiguity. Proven ability to work cross-functionally, bridging the gap between security and broader technology teams to demonstrably improve the overall security posture. Desirable skills and experience: Scripting and automation capabilities, particularly utilising Python, PySpark, and SQL to streamline analytical workflows. Experience navigating cloud-native security environments (AWS, Azure, or GCP) alongside familiarity with the Microsoft 365 ecosystem. Advanced knowledge of offensive security methodologies, including common exploit chains, reverse engineering basics, or penetration testing techniques. Relevant industry certifications demonstrating specialised knowledge in threat hunting, incident response, or forensics (e.g., SANS GCIA, GCIH, GCFA, OSCP). Benefits and perks There's one thing people can't stop talking about when it comes to life at Sky: the perks . Here's a taster: Free Sky TV or NOW package, including Sky Sports and Sky Cinema Pension package with up to 9% employer contribution Private healthcare with mental health support Aviva Digital GP and dental insurance Discounts on Sky products, including Sky Mobile, Sky Broadband, Sky Glass and Sky Protect Sharesave and Tech schemes A range of Sky VIP rewards and experiences How you'll work Osterley The hybrid working expectations for this role are 2 days in the office per week. Our Sky Group HQ. Equipped with state-of-the-art technology and workspaces, there's plenty of space to see your big ideas come to life. Here you'll find 13 subsidised restaurants and cafes. You can re-energise at our gym, catch the latest films at our cinema, get your car washed and even get pampered at our beauty salon . Our Osterley Campus is just a 10-minute walk from Syon Lane train station, or you can get one of our free shuttle buses from Osterley, Gunnersbury and Ealing Broadway stations. Plus, there's free onsite parking available for cars, motorbikes and bicycles. Who we are We're Sky, a leading media and entertainment company who connect millions with entertainment, sports, news and arts through innovative products and services. Working with us means you'll be bringing the joy of a better experience to more people, every day. All so we can do better and deliver better for our customers, colleagues and society. We're an equal opportunity employer and value diversity at our company. We're a Disability Confident Accredited Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all and will make reasonable adjustments to support you where appropriate . Please flag any adjustments you need as early as you can. Just so you know: if your application is successful, we'll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer. To be eligible for this role you are required to have the appropriate right to work in the UK. Please be aware Sky does not offer sponsorship for this position. To find out more about working with us, search on social media.
23/06/2026
Full time
We don't just believe in better. We make it happen. Better content. Better products. And better careers. Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, Sky Stream to Sky Glass, we never stand still. We optimise and innovate. We turn big ideas into the products, content and services millions of people love. And we do it all right here at Sky. Role overview Our products, platforms and technologies are constantly evolving that's why keeping Sky safe from cyber-attacks is one of our top priorities. Our Cyber Security team helps the business grow while protecting our customers, colleagues and partners from increasingly sophisticated cyber threats. Our team includes Cyber Fusion Centre, Security Services, Risk and Compliance, Programme Delivery and Business Security, and we work across the UK, Italy and Germany. Join us and you'll get involved in tackling challenges and future threats in an ever-changing cyber landscape. You will join our comprehensive Cyber Defence Department as a senior member of the dedicated Threat Hunt team. You will operate within a robust security ecosystem, partnering directly with Cyber Operations, Threat Intelligence, Engineering, and Threat Vulnerability Management. What you'll do : Conduct proactive threat hunts across the enterprise, broadcast, and telco networks to identify abnormal activity, emerging attack techniques, and advanced threats. Develop and execute hypothesis-driven threat hunts utilising datasets across a variety of security tooling, including EDR, SIEM, and network-layer defences. Collaborate directly with the Cyber Threat Intelligence team to operationalise intelligence, maintaining and refining hunting playbooks for priority threat actors and relevant TTPs. Partner with security engineering teams to translate hunt findings into productionised, high-fidelity detections and drive continuous improvement in data source coverage and quality. Act as a technical mentor within the Cyber Defence function, guiding junior analysts, conducting peer reviews, and fostering a culture of continuous learning. Document and communicate hunt outcomes comprehensively, translating complex technical findings into actionable remediation strategies and executive-level summaries. What you'll bring : Essential Criteria Extensive prior experience in threat hunting at a large enterprise environment. Experience with incident response, SOC, or detection engineering. Deep understanding of the MITRE ATT&CK framework and how to practically apply it to threat hunting methodologies and detection logic. Proficiency in complex query writing (e.g., KQL, SPL, SQL) to filter, analyse, and visualise large, disparate datasets. Hands-on experience with EDR, NDR, SIEM, SOAR security platforms and data analysis platforms such as Databricks. Strong investigative acumen combined with a curious, highly analytical mindset capable of navigating ambiguity. Proven ability to work cross-functionally, bridging the gap between security and broader technology teams to demonstrably improve the overall security posture. Desirable skills and experience: Scripting and automation capabilities, particularly utilising Python, PySpark, and SQL to streamline analytical workflows. Experience navigating cloud-native security environments (AWS, Azure, or GCP) alongside familiarity with the Microsoft 365 ecosystem. Advanced knowledge of offensive security methodologies, including common exploit chains, reverse engineering basics, or penetration testing techniques. Relevant industry certifications demonstrating specialised knowledge in threat hunting, incident response, or forensics (e.g., SANS GCIA, GCIH, GCFA, OSCP). Benefits and perks There's one thing people can't stop talking about when it comes to life at Sky: the perks . Here's a taster: Free Sky TV or NOW package, including Sky Sports and Sky Cinema Pension package with up to 9% employer contribution Private healthcare with mental health support Aviva Digital GP and dental insurance Discounts on Sky products, including Sky Mobile, Sky Broadband, Sky Glass and Sky Protect Sharesave and Tech schemes A range of Sky VIP rewards and experiences How you'll work Osterley The hybrid working expectations for this role are 2 days in the office per week. Our Sky Group HQ. Equipped with state-of-the-art technology and workspaces, there's plenty of space to see your big ideas come to life. Here you'll find 13 subsidised restaurants and cafes. You can re-energise at our gym, catch the latest films at our cinema, get your car washed and even get pampered at our beauty salon . Our Osterley Campus is just a 10-minute walk from Syon Lane train station, or you can get one of our free shuttle buses from Osterley, Gunnersbury and Ealing Broadway stations. Plus, there's free onsite parking available for cars, motorbikes and bicycles. Who we are We're Sky, a leading media and entertainment company who connect millions with entertainment, sports, news and arts through innovative products and services. Working with us means you'll be bringing the joy of a better experience to more people, every day. All so we can do better and deliver better for our customers, colleagues and society. We're an equal opportunity employer and value diversity at our company. We're a Disability Confident Accredited Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all and will make reasonable adjustments to support you where appropriate . Please flag any adjustments you need as early as you can. Just so you know: if your application is successful, we'll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer. To be eligible for this role you are required to have the appropriate right to work in the UK. Please be aware Sky does not offer sponsorship for this position. To find out more about working with us, search on social media.
Choose a partner with intimate knowledge of your industry and first-hand experience of defining its future.Your locationYour locationIndustriesChoose a partner with intimate knowledge of your industry and first-hand experience of defining its future.Birmingham, London, Bristol, Newcastle, Manchester# Data EngineerThe Data Platforms team is part of the Insights and Data Global Practice and has seen strong growth and continued success across a variety of projects and sectors. Data Platforms is the home of the Data Engineers, Platform Engineers, Solutions Architects and Business Analysts who are focused on driving our customers digital and data transformation journey using the modern cloud platforms.We specialise on using the latest frameworks, reference architectures and technologies using AWS, Azure and GCP along with various data platforms like Databricks, Snowflake, Quantexa, Palantir, SAS. The Role You Are Considering As a Data Engineer, you will be an integral part of our team dedicated to building scalable and secure data platforms. You will leverage your expertise to design, develop, and implement data warehouses, data lakehouses, and AI/ML models that fuel our data-driven operations. Design and build high-performance data pipelines: to extract, transform, and load data into Cloud Data Lake Storage and other Cloud services. Develop and maintain secure data warehouses and data lakehouses: Implement data models, data quality checks, and governance practices to ensure reliable and accurate data. Implement ETL/ELT Processes: Develop Extract, Transform, Load (ETL) or Extract, Load, Transform (ELT) workflows to seamlessly move data from source systems to Data Warehouses, Data Lakes, and Lake Houses using Open Source and cloud tools.In addition to these core skills, you should have specialist experience in one or more of the following technologies Azure Databricks Design and build high-performance data pipelines: Utilize Databricks and Apache Spark to extract, transform, and load data into Azure Data Lake Storage and other Azure services. Experience of Databricks ML and Azure ML to develop predictive models and drive business insights. Proven expertise in Databricks, Apache Spark, and data pipeline development and strong understanding of data warehousing concepts and practices. Experience with Microsoft Azure cloud platform, including Azure Data Lake Storage, Databricks and Azure Data Factory. Azure Data Engineer Associate and Databricks Certified Data Engineer Professional AWS Proficiency with AWS Tools: Demonstrable experience using AWS Glue, AWS Lambda, Amazon Kinesis, Amazon EMR , Amazon Athena, Amazon DynamoDB, Amazon Cloudwatch, Amazon SNS and AWS Step Functions. Programming Skills: Strong experience with modern programming languages such as Python, Java, Scala & Pyspark. Expertise in Data Storage Technologies: In-depth knowledge of Data Warehouse, Database technologies, and Big Data Eco-system technologies such as AWS Redshift, AWS RDS, and Hadoop. Experience with AWS Data Lakes: Proven experience working with AWS data lakes on AWS S3 to store and process both structured and unstructured data sets Build and deploy AI/ML models: Integrate Machine Learning into data pipelines, leveraging ML to develop predictive models and drive business insights. Monitor and optimize data pipelines and infrastructure: Analyze performance metrics, identify bottlenecks, and implement optimizations for efficiency and scalability. Collaborate with cross-functional teams: Work closely with business analysts, data scientists, and DevOps engineers to ensure successful data platform implementations. Stay ahead of the curve: Continuously learn and adapt to the evolving landscape of big data technologies and best practices with a focus on how AI can support you in your delivery work Minimum 10+ years of experience as a Data Engineer or similar role. Proven expertise in the technologies below, and data pipeline development and strong understanding of data warehousing concepts and practices. Excellent problem-solving and analytical skills and strong communication and teamwork skills.Security Clearance: To be successfully appointed to this role, must be eligible to obtain Security Check (SC)clearance. To obtain SC clearance, the successful applicant must have resided continuously within the United Kingdom for the last 5 years, along with other criteria and requirements.Throughout the recruitment process, you will be asked questions about your security clearance eligibility such as, but not limited to, country of residence and nationality. Some posts are restricted to sole UK Nationals for security reasons; therefore, you may be asked about your citizenship in the application process.Hybrid working: The places that you work from day to day will vary according to your role, your needs, and those of the business; it will be a blend of Company offices, client sites, and your home; noting that you will be unable to work at home 100% of the time.If you are successfully offered this position, you will go through a series of pre-employment checks, including: identity, nationality (single or dual) or immigration status, employment history going back 3 continuous years, and unspent criminal record check (known as Disclosure and Barring Service) What we'll offer you You will be encouraged to have a positive work-life balance. Our hybrid-first way of working means we embed hybrid working in all that we do and make flexible working arrangements the day-to-day reality for our people. All UK employees are eligible to request flexible working arrangements.You will be empowered to explore, innovate, and progress. You will benefit from Capgemini's 'learning for life' mindset, meaning you will have countless training and development opportunities from thinktanks to hackathons, and access to 250,000 courses with numerous external certifications from AWS, Microsoft, Harvard Manage Mentor, Cybersecurity qualifications and much more. Why we're different At Capgemini, we help organisations across the world become more agile, more competitive, and more successful. Smart, tailored, often ground-breaking technical solutions to complex problems are the norm. But so, too, is a culture that's as collaborative as it is forward thinking. Working closely with each other, and with our clients, we get under the skin of businesses and to the heart of their goals. You will too. Capgemini is proud to represent nearly 130 nationalities and its cultural diversity. Our holistic definition of diversity extends beyond gender, gender identity, sexual orientation, disability, ethnicity, race, age, and religion. Capgemini views diversity as everything that makes us who we are as an organization, including our social background, our experiences in life and work, our communication styles and even our personality. These dimensions contribute to the type of diversity we value the most: diversity of thought.Experience levelExperienced ProfessionalsLocationBirmingham, London, Bristol, Newcastle, Manchester
23/06/2026
Full time
Choose a partner with intimate knowledge of your industry and first-hand experience of defining its future.Your locationYour locationIndustriesChoose a partner with intimate knowledge of your industry and first-hand experience of defining its future.Birmingham, London, Bristol, Newcastle, Manchester# Data EngineerThe Data Platforms team is part of the Insights and Data Global Practice and has seen strong growth and continued success across a variety of projects and sectors. Data Platforms is the home of the Data Engineers, Platform Engineers, Solutions Architects and Business Analysts who are focused on driving our customers digital and data transformation journey using the modern cloud platforms.We specialise on using the latest frameworks, reference architectures and technologies using AWS, Azure and GCP along with various data platforms like Databricks, Snowflake, Quantexa, Palantir, SAS. The Role You Are Considering As a Data Engineer, you will be an integral part of our team dedicated to building scalable and secure data platforms. You will leverage your expertise to design, develop, and implement data warehouses, data lakehouses, and AI/ML models that fuel our data-driven operations. Design and build high-performance data pipelines: to extract, transform, and load data into Cloud Data Lake Storage and other Cloud services. Develop and maintain secure data warehouses and data lakehouses: Implement data models, data quality checks, and governance practices to ensure reliable and accurate data. Implement ETL/ELT Processes: Develop Extract, Transform, Load (ETL) or Extract, Load, Transform (ELT) workflows to seamlessly move data from source systems to Data Warehouses, Data Lakes, and Lake Houses using Open Source and cloud tools.In addition to these core skills, you should have specialist experience in one or more of the following technologies Azure Databricks Design and build high-performance data pipelines: Utilize Databricks and Apache Spark to extract, transform, and load data into Azure Data Lake Storage and other Azure services. Experience of Databricks ML and Azure ML to develop predictive models and drive business insights. Proven expertise in Databricks, Apache Spark, and data pipeline development and strong understanding of data warehousing concepts and practices. Experience with Microsoft Azure cloud platform, including Azure Data Lake Storage, Databricks and Azure Data Factory. Azure Data Engineer Associate and Databricks Certified Data Engineer Professional AWS Proficiency with AWS Tools: Demonstrable experience using AWS Glue, AWS Lambda, Amazon Kinesis, Amazon EMR , Amazon Athena, Amazon DynamoDB, Amazon Cloudwatch, Amazon SNS and AWS Step Functions. Programming Skills: Strong experience with modern programming languages such as Python, Java, Scala & Pyspark. Expertise in Data Storage Technologies: In-depth knowledge of Data Warehouse, Database technologies, and Big Data Eco-system technologies such as AWS Redshift, AWS RDS, and Hadoop. Experience with AWS Data Lakes: Proven experience working with AWS data lakes on AWS S3 to store and process both structured and unstructured data sets Build and deploy AI/ML models: Integrate Machine Learning into data pipelines, leveraging ML to develop predictive models and drive business insights. Monitor and optimize data pipelines and infrastructure: Analyze performance metrics, identify bottlenecks, and implement optimizations for efficiency and scalability. Collaborate with cross-functional teams: Work closely with business analysts, data scientists, and DevOps engineers to ensure successful data platform implementations. Stay ahead of the curve: Continuously learn and adapt to the evolving landscape of big data technologies and best practices with a focus on how AI can support you in your delivery work Minimum 10+ years of experience as a Data Engineer or similar role. Proven expertise in the technologies below, and data pipeline development and strong understanding of data warehousing concepts and practices. Excellent problem-solving and analytical skills and strong communication and teamwork skills.Security Clearance: To be successfully appointed to this role, must be eligible to obtain Security Check (SC)clearance. To obtain SC clearance, the successful applicant must have resided continuously within the United Kingdom for the last 5 years, along with other criteria and requirements.Throughout the recruitment process, you will be asked questions about your security clearance eligibility such as, but not limited to, country of residence and nationality. Some posts are restricted to sole UK Nationals for security reasons; therefore, you may be asked about your citizenship in the application process.Hybrid working: The places that you work from day to day will vary according to your role, your needs, and those of the business; it will be a blend of Company offices, client sites, and your home; noting that you will be unable to work at home 100% of the time.If you are successfully offered this position, you will go through a series of pre-employment checks, including: identity, nationality (single or dual) or immigration status, employment history going back 3 continuous years, and unspent criminal record check (known as Disclosure and Barring Service) What we'll offer you You will be encouraged to have a positive work-life balance. Our hybrid-first way of working means we embed hybrid working in all that we do and make flexible working arrangements the day-to-day reality for our people. All UK employees are eligible to request flexible working arrangements.You will be empowered to explore, innovate, and progress. You will benefit from Capgemini's 'learning for life' mindset, meaning you will have countless training and development opportunities from thinktanks to hackathons, and access to 250,000 courses with numerous external certifications from AWS, Microsoft, Harvard Manage Mentor, Cybersecurity qualifications and much more. Why we're different At Capgemini, we help organisations across the world become more agile, more competitive, and more successful. Smart, tailored, often ground-breaking technical solutions to complex problems are the norm. But so, too, is a culture that's as collaborative as it is forward thinking. Working closely with each other, and with our clients, we get under the skin of businesses and to the heart of their goals. You will too. Capgemini is proud to represent nearly 130 nationalities and its cultural diversity. Our holistic definition of diversity extends beyond gender, gender identity, sexual orientation, disability, ethnicity, race, age, and religion. Capgemini views diversity as everything that makes us who we are as an organization, including our social background, our experiences in life and work, our communication styles and even our personality. These dimensions contribute to the type of diversity we value the most: diversity of thought.Experience levelExperienced ProfessionalsLocationBirmingham, London, Bristol, Newcastle, Manchester
Role Overview We are seeking a highly analytical and technically capable Data Analyst to support the development of a data-driven claims function. This role will report directly to the Head of Claims and will work closely with TPAs, and Vave's Underwriting, Operations, and Technology teams. The Data Analyst will be responsible for extracting, analysing, reconciling, and interpreting claims data to support operational oversight, reserving discipline, TPA performance, underwriting feedback, and portfolio profitability. The ideal candidate will have strong experience with SQL, Excel, data validation, reporting and claims analysis. This is a hands on role for someone who can transform data into insight, and help the business make better claims, underwriting, and financial decisions. Data Analysis Analyse claims data from internal systems, TPAs data feeds, bordereaux reports, and data warehouses. Use SQL to query claims databases, validate data quality, build recurring extracts, and support ad,hoc analysis. Work within an Azure Databricks environment, utilising SQL, and Python skills to automate claims analysis and oversight reporting. Operational reporting, severity analysis, reserving reviews, claims feedback for underwriting. Identify and investigate data quality concerns. Translate claims data into clear insights, trends, exceptions, and recommended actions. Claims MI, Reporting & Dashboards Shape recurring claims management information, dashboards, KPI packs, and executive reporting. Track and report on key claim metrics. Support the creation of board, capacity partner, underwriting, and actuarial reporting packs. Actuarial & Underwriting Support Support reserve reviews, loss development analysis, large loss monitoring, data reconciliations, and claims trend analysis. Partner with Underwriting to provide claim insights that inform risk selection, pricing, appetite, policy wording, exclusions, endorsement, and portfolio strategy. Support development of claims feedback loops that connect loss experience back to underwriting action. Rules Engine, Scoring & Claims Intelligence Support the build out of claims rules, escalation triggers, severity scoring models and exception reporting. Participate in UAT for claims systems, rules engines, dashboards, portals, data feeds, and workflow tools. Translate business requirements from Claims into technical data logic, SQL predicates, reporting rules, and test cases. Required Experience 3+ years of experience in data analytics within the financial/insurance sector. Ability to work with incomplete, inconsistent, or complex data sources. Strong SQL querying and data manipulation skills. Advanced Excel and data reconciliation skills. Experience working within Azure Databricks (preferred), using notebooks to analyse and transform data, and leveraging Azure data services such as Azure SQL, Data Lake Storage, and cloud based data platforms. Experience extracting and analysing data from systems or reporting platforms, including Lloyd's/delegated authority bordereaux. Demonstrated ability to analyse complex datasets and present findings in a clear, concise, business relevant manner. Preferred Experience Prior experience with a TPA, MGA, MGU, insurance carrier, or reinsurer within a delegated authority business. Experience working with Actuarial and Underwriting teams. Familiarity with claims bordereaux, delegated authority reporting, capacity partner reporting, or reinsurance reporting. Experience with Databricks, Synapse, or similar analytics tools. Understanding of claims leakage, severity management, reserve adequacy, litigation trends, fraud indicators, subrogation, and vendor performance.
23/06/2026
Full time
Role Overview We are seeking a highly analytical and technically capable Data Analyst to support the development of a data-driven claims function. This role will report directly to the Head of Claims and will work closely with TPAs, and Vave's Underwriting, Operations, and Technology teams. The Data Analyst will be responsible for extracting, analysing, reconciling, and interpreting claims data to support operational oversight, reserving discipline, TPA performance, underwriting feedback, and portfolio profitability. The ideal candidate will have strong experience with SQL, Excel, data validation, reporting and claims analysis. This is a hands on role for someone who can transform data into insight, and help the business make better claims, underwriting, and financial decisions. Data Analysis Analyse claims data from internal systems, TPAs data feeds, bordereaux reports, and data warehouses. Use SQL to query claims databases, validate data quality, build recurring extracts, and support ad,hoc analysis. Work within an Azure Databricks environment, utilising SQL, and Python skills to automate claims analysis and oversight reporting. Operational reporting, severity analysis, reserving reviews, claims feedback for underwriting. Identify and investigate data quality concerns. Translate claims data into clear insights, trends, exceptions, and recommended actions. Claims MI, Reporting & Dashboards Shape recurring claims management information, dashboards, KPI packs, and executive reporting. Track and report on key claim metrics. Support the creation of board, capacity partner, underwriting, and actuarial reporting packs. Actuarial & Underwriting Support Support reserve reviews, loss development analysis, large loss monitoring, data reconciliations, and claims trend analysis. Partner with Underwriting to provide claim insights that inform risk selection, pricing, appetite, policy wording, exclusions, endorsement, and portfolio strategy. Support development of claims feedback loops that connect loss experience back to underwriting action. Rules Engine, Scoring & Claims Intelligence Support the build out of claims rules, escalation triggers, severity scoring models and exception reporting. Participate in UAT for claims systems, rules engines, dashboards, portals, data feeds, and workflow tools. Translate business requirements from Claims into technical data logic, SQL predicates, reporting rules, and test cases. Required Experience 3+ years of experience in data analytics within the financial/insurance sector. Ability to work with incomplete, inconsistent, or complex data sources. Strong SQL querying and data manipulation skills. Advanced Excel and data reconciliation skills. Experience working within Azure Databricks (preferred), using notebooks to analyse and transform data, and leveraging Azure data services such as Azure SQL, Data Lake Storage, and cloud based data platforms. Experience extracting and analysing data from systems or reporting platforms, including Lloyd's/delegated authority bordereaux. Demonstrated ability to analyse complex datasets and present findings in a clear, concise, business relevant manner. Preferred Experience Prior experience with a TPA, MGA, MGU, insurance carrier, or reinsurer within a delegated authority business. Experience working with Actuarial and Underwriting teams. Familiarity with claims bordereaux, delegated authority reporting, capacity partner reporting, or reinsurance reporting. Experience with Databricks, Synapse, or similar analytics tools. Understanding of claims leakage, severity management, reserve adequacy, litigation trends, fraud indicators, subrogation, and vendor performance.
Job Overview Data Analyst, Analytics & Insights - reporting to Regional Analytics Manager. Betway is part of Super Group, the NYSE listed digital gaming company behind leading Sports and iGaming brands. We aim to become the global leader in online sports betting and casino gaming. Responsibilities Answer business questions from stakeholders across a wide range of departments. Address analysis requests and provide actionable insights. Build reports, dashboards, models, and proof of concepts. Partner with relevant teams to determine campaign effectiveness using performance data. Assist the marketing team in determining ROI and monetary impact of acquisition efforts. Improve the flow of reporting, explanations and rationale; explain performance to relevant stakeholders. Maintain knowledge, expertise and best practices on a suite of data and BI technologies to promote appropriate adoption with the team. Stay up to date on the latest technologies and best practices. This job description is not intended to be an exhaustive list of responsibilities. You may be required to complete other reasonable duties to achieve business objectives. Essential Qualifications Degree level qualification in a numeric, data prominent discipline or similar. At least three years of work experience in a data analytics or business intelligence role. Experience with Tableau, PowerBI, or other data visualisation tools. Demonstrable SQL skills to query complex data sets for analysis. Demonstrable analytical and report development abilities. Strong communication and presentation skills. Ability to convey concepts, analysis and insights to technical and non technical audiences. Ability to develop and sustain relationships with key stakeholders and peers. Ability to analyse large amounts of data quickly and accurately. Ability to manage a challenging workload while working quickly and precisely under pressure. Passionate about data. Desirable Qualifications Experience working in online gaming or casino industry. Knowledge of online casino and sports betting. Proficiency in Excel or other data analysis tools. Experience using Databricks. Experience with other BI tools such as Alteryx. Experience using Google Analytics for reporting and analysis, including BigQuery. Core Values Adaptability Ownership and accountability Initiating action Resilience Team orientation Integrity Innovation Benefits Comprehensive learning and development programmes. Performance Tool that provides regular feedback and supports career growth. Employee Assistance Programme offering benefits such as: Vitality Health Care Unum Dental Life Assurance & Income Protection Tusker car scheme Cycle to Work Retail discounts
23/06/2026
Full time
Job Overview Data Analyst, Analytics & Insights - reporting to Regional Analytics Manager. Betway is part of Super Group, the NYSE listed digital gaming company behind leading Sports and iGaming brands. We aim to become the global leader in online sports betting and casino gaming. Responsibilities Answer business questions from stakeholders across a wide range of departments. Address analysis requests and provide actionable insights. Build reports, dashboards, models, and proof of concepts. Partner with relevant teams to determine campaign effectiveness using performance data. Assist the marketing team in determining ROI and monetary impact of acquisition efforts. Improve the flow of reporting, explanations and rationale; explain performance to relevant stakeholders. Maintain knowledge, expertise and best practices on a suite of data and BI technologies to promote appropriate adoption with the team. Stay up to date on the latest technologies and best practices. This job description is not intended to be an exhaustive list of responsibilities. You may be required to complete other reasonable duties to achieve business objectives. Essential Qualifications Degree level qualification in a numeric, data prominent discipline or similar. At least three years of work experience in a data analytics or business intelligence role. Experience with Tableau, PowerBI, or other data visualisation tools. Demonstrable SQL skills to query complex data sets for analysis. Demonstrable analytical and report development abilities. Strong communication and presentation skills. Ability to convey concepts, analysis and insights to technical and non technical audiences. Ability to develop and sustain relationships with key stakeholders and peers. Ability to analyse large amounts of data quickly and accurately. Ability to manage a challenging workload while working quickly and precisely under pressure. Passionate about data. Desirable Qualifications Experience working in online gaming or casino industry. Knowledge of online casino and sports betting. Proficiency in Excel or other data analysis tools. Experience using Databricks. Experience with other BI tools such as Alteryx. Experience using Google Analytics for reporting and analysis, including BigQuery. Core Values Adaptability Ownership and accountability Initiating action Resilience Team orientation Integrity Innovation Benefits Comprehensive learning and development programmes. Performance Tool that provides regular feedback and supports career growth. Employee Assistance Programme offering benefits such as: Vitality Health Care Unum Dental Life Assurance & Income Protection Tusker car scheme Cycle to Work Retail discounts
Job Title: Data Engineer Location: Long Stratton, Norfolk NR15 (Hybrid - Fortnightly Office Attendance) Contract: Permanent Hours: Full time (37 hours per week) Salary: £63,000 per annum About the Role This is an opportunity to join a growing Data & Analytics team and take ownership of a modern Azure data platform. You'll be responsible for building and maintaining data pipelines, developing data warehouse solutions, and supporting the organisation's move towards Microsoft Fabric. Responsibilities Design, build and maintain a scalable Azure-based data warehouse to support reporting, analytics and business intelligence requirements. Develop and maintain robust ETL/ELT processes, data integration frameworks and transformation pipelines using Azure Data Factory, Azure Synapse and Microsoft Fabric technologies. Support the implementation, optimisation and ongoing development of Microsoft Fabric, including Lakehouse, Warehouse, Data Engineering and Data Pipeline capabilities. Design and maintain efficient data models, ensuring data structures support both operational and analytical reporting requirements. Build reusable, parameterised and scalable data pipelines that integrate data from multiple internal and external sources. Monitor and maintain data pipelines, implementing automated alerting, logging and performance monitoring to ensure platform reliability. Work closely with BI Analysts and business stakeholders to understand data requirements and deliver scalable engineering solutions. Implement data quality controls, validation rules and automated testing processes to improve data accuracy and consistency. Support the development and maintenance of data governance standards, metadata management and technical documentation. Ensure compliance with GDPR and data security requirements across all data solutions. Contribute to cloud infrastructure decisions, platform optimisation and storage strategies to maximise performance and cost efficiency. Utilise Azure DevOps and Git to support CI/CD processes, version control and automated deployments. Provide technical guidance to colleagues and promote best practice across data engineering and platform development. Drive continuous improvement initiatives and identify opportunities to automate manual processes and enhance data accessibility across the organisation. Requirements Proven experience working as a Data Engineer, Azure Data Engineer, ETL Developer or similar role. Advanced SQL skills, including writing, optimising and troubleshooting complex queries, stored procedures and data transformations. Strong experience designing and building ETL/ELT pipelines using Azure Data Factory, Azure Synapse, Databricks, Airflow or similar technologies. Hands on experience working with Azure cloud data platforms, including Data Lake, Synapse Analytics and related services. Strong understanding of data warehousing concepts and data modelling methodologies, including star schema and dimensional modelling techniques. Experience designing scalable data architectures and integrating data from multiple systems and applications. Knowledge of CI/CD processes, source control and deployment automation using Azure DevOps, Git or similar tools. Experience implementing data quality, validation and monitoring processes. Strong understanding of data governance, security principles and GDPR requirements. Excellent problem solving skills with the ability to identify root causes and implement long term solutions. Strong communication skills with the ability to engage effectively with both technical and non technical stakeholders. Ability to manage multiple priorities and deliver high quality solutions within agreed timescales. Desirable Experience working with Microsoft Fabric, including Lakehouse, Warehouse and Data Pipelines. Knowledge of Python and/or Scala for data engineering and automation. Experience with Docker, Kubernetes or other containerisation technologies. Exposure to machine learning pipelines or MLOps frameworks. Experience with data quality frameworks such as Great Expectations. Knowledge of Dynamics365 or housing management systems. Microsoft Azure, SQL or Data Engineering certifications.
23/06/2026
Full time
Job Title: Data Engineer Location: Long Stratton, Norfolk NR15 (Hybrid - Fortnightly Office Attendance) Contract: Permanent Hours: Full time (37 hours per week) Salary: £63,000 per annum About the Role This is an opportunity to join a growing Data & Analytics team and take ownership of a modern Azure data platform. You'll be responsible for building and maintaining data pipelines, developing data warehouse solutions, and supporting the organisation's move towards Microsoft Fabric. Responsibilities Design, build and maintain a scalable Azure-based data warehouse to support reporting, analytics and business intelligence requirements. Develop and maintain robust ETL/ELT processes, data integration frameworks and transformation pipelines using Azure Data Factory, Azure Synapse and Microsoft Fabric technologies. Support the implementation, optimisation and ongoing development of Microsoft Fabric, including Lakehouse, Warehouse, Data Engineering and Data Pipeline capabilities. Design and maintain efficient data models, ensuring data structures support both operational and analytical reporting requirements. Build reusable, parameterised and scalable data pipelines that integrate data from multiple internal and external sources. Monitor and maintain data pipelines, implementing automated alerting, logging and performance monitoring to ensure platform reliability. Work closely with BI Analysts and business stakeholders to understand data requirements and deliver scalable engineering solutions. Implement data quality controls, validation rules and automated testing processes to improve data accuracy and consistency. Support the development and maintenance of data governance standards, metadata management and technical documentation. Ensure compliance with GDPR and data security requirements across all data solutions. Contribute to cloud infrastructure decisions, platform optimisation and storage strategies to maximise performance and cost efficiency. Utilise Azure DevOps and Git to support CI/CD processes, version control and automated deployments. Provide technical guidance to colleagues and promote best practice across data engineering and platform development. Drive continuous improvement initiatives and identify opportunities to automate manual processes and enhance data accessibility across the organisation. Requirements Proven experience working as a Data Engineer, Azure Data Engineer, ETL Developer or similar role. Advanced SQL skills, including writing, optimising and troubleshooting complex queries, stored procedures and data transformations. Strong experience designing and building ETL/ELT pipelines using Azure Data Factory, Azure Synapse, Databricks, Airflow or similar technologies. Hands on experience working with Azure cloud data platforms, including Data Lake, Synapse Analytics and related services. Strong understanding of data warehousing concepts and data modelling methodologies, including star schema and dimensional modelling techniques. Experience designing scalable data architectures and integrating data from multiple systems and applications. Knowledge of CI/CD processes, source control and deployment automation using Azure DevOps, Git or similar tools. Experience implementing data quality, validation and monitoring processes. Strong understanding of data governance, security principles and GDPR requirements. Excellent problem solving skills with the ability to identify root causes and implement long term solutions. Strong communication skills with the ability to engage effectively with both technical and non technical stakeholders. Ability to manage multiple priorities and deliver high quality solutions within agreed timescales. Desirable Experience working with Microsoft Fabric, including Lakehouse, Warehouse and Data Pipelines. Knowledge of Python and/or Scala for data engineering and automation. Experience with Docker, Kubernetes or other containerisation technologies. Exposure to machine learning pipelines or MLOps frameworks. Experience with data quality frameworks such as Great Expectations. Knowledge of Dynamics365 or housing management systems. Microsoft Azure, SQL or Data Engineering certifications.
Job Title: Data Architect - Azure Databricks / Azure Data Factory For London Market InsuranceExp Required - 10 years PlusLocation: LondonAbout the Job you are considering:We are looking for an experienced Data Architect with strong expertise in Azure Databricks, Azure Data Factory, Azure Data Lake, Delta Lake, data modelling, data governance, and cloud data architecture, along with domain experience in London Market Insurance.The candidate will be responsible for defining and delivering scalable data architecture solutions for insurance transformation programmes covering underwriting, claims, policy administration, bordereaux, delegated authority, premium processing, regulatory reporting, reinsurance, analytics, and data migration.The ideal candidate should have strong hands-on architecture experience in Azure-based data platforms and should be able to work closely with business stakeholders, enterprise architects, solution architects, data engineers, insurance SMEs, vendors, and delivery teamsHybrid working:The places that you work from day to day will vary according to your role, your needs, and those of the business; it will be a blend of Company offices, client sites, and your home; noting that you will be unable to work at home 100% of the time.Key Responsibilities:Define end-to-end data architecture for Azure-based data platforms using Azure Databricks, Azure Data Factory, ADLS Gen2, Delta Lake, Azure Synapse, and Power BI.Design scalable and secure lakehouse architecture using bronze, silver, and gold data layers.Lead architecture and design for data ingestion, transformation, curation, data marts, reporting, and analytics solutions.Create high-level and low-level data architecture documents, data flow diagrams, integration architecture, and data platform blueprints.Define architecture patterns for batch, incremental, real-time, and API-based data ingestion.Design reusable data ingestion and transformation frameworks using ADF and Databricks.Define data models for London Market Insurance data including policy, claims, premium, broker, bordereaux, delegated authority, reinsurance, exposure, and regulatory reporting data.Work with business analysts and insurance SMEs to understand London Market business processes and translate requirements into data architecture.Define standards for data modelling, source-to-target mapping, data quality, reconciliation, metadata, lineage, and auditability.Design data governance, security, access control, and compliance frameworks for insurance data.Support cloud migration, data warehouse modernisation, reporting transformation, and legacy system decommissioning initiatives.Review technical designs, data models, ETL/ELT pipelines, and engineering implementation.Provide architectural guidance to data engineers working on Azure Databricks, ADF, PySpark, SQL, and Delta Lake.Collaborate with enterprise architecture, solution architecture, security, infrastructure, DevOps, and business teams.Define CI/CD, DevOps, deployment, monitoring, and operational support architecture for data platforms.Identify performance, scalability, reliability, and cost optimisation opportunities across Azure data services.Support governance forums, architecture review boards, design authority meetings, and client stakeholder workshops.Mandatory SkillsStrong experience as a Data Architect or Senior Data Architect.Strong hands-on experience with Azure Databricks.Strong architecture and implementation experience with Azure Data Factory.Strong understanding of Azure Data Lake Storage Gen2.Strong experience with Delta Lake, lakehouse architecture, and medallion architecture.Excellent knowledge of data modelling, dimensional modelling, canonical data models, and enterprise data models.Strong experience in designing ETL/ELT data pipelines.Good understanding of PySpark, Spark SQL, Python, and SQL.Strong knowledge of data warehouse, data lake, data mart, and semantic layer architecture.Experience in defining data quality, data validation, reconciliation, audit, and exception handling frameworks.Experience with data governance, metadata management, data lineage, data catalogue, and data privacy controls.Experience with Azure security concepts including Managed Identity, Azure RBAC, Key Vault, ACLs, private endpoints, and encryption.Experience with CI/CD and DevOps practices using Azure DevOps, Git, ARM templates, Bicep, or Terraform.Strong stakeholder management, communication, presentation, and documentation skills.Ability to lead architecture discussions with business, technology, and senior client stakeholders.London Market Insurance Domain ExperienceThe candidate should have exposure to one or more of the following areas:Lloyd's Market operationsLondon Market Insurance operating modelSpecialty insurance and commercial insuranceBroker, carrier, managing agent, and syndicate data flowsUnderwriting data architectureClaims data architecturePolicy administration dataPremium and claims accountingBordereaux processingDelegated authority and binder dataCoverholder dataExposure managementReinsurance dataRegulatory and compliance reportingFinancial and management reportingBlueprint Two / London Market modernisation data initiativesAzure Architecture Skills ExpectedCandidate should have strong knowledge of the following Azure components:Azure DatabricksLakehouse architectureDatabricks notebooks, jobs, workflows, clustersDelta Lake optimisationUnity Catalog, if applicableDatabricks SQL, if applicableCluster sizing and cost optimisationSecurity and access control patternsAzure Data FactoryPipeline orchestrationLinked services and datasetsIntegration runtimeParameterised pipelinesTriggers and schedulingError handling and retry patternsMetadata-driven ingestion frameworksMonitoring and operational supportAzure Data Lake / StorageADLS Gen2 architectureLanding, raw, curated, and consumption zonesFolder hierarchy and naming standardsPartitioning strategyFile format standardsData retention and archival strategyAzure Governance and SecurityAzure Key VaultManaged IdentityAzure RBACStorage ACLsPrivate endpointsData maskingEncryption at rest and in transitLogging, monitoring, and audit controlsData Architecture ResponsibilitiesDefine conceptual, logical, and physical data models.Design canonical data models for insurance entities.Define data domains such as policy, claims, party, broker, premium, risk, exposure, and reinsurance.Define source-to-target mapping standards.Establish data quality rules and validation patterns.Define metadata and lineage requirements.Design reusable data ingestion frameworks.Define data retention, archival, and purge strategies.Define master and reference data management approach.Design reporting and analytics data marts.Define semantic layer and consumption patterns for BI tools.Review and approve data engineering designs and implementation.We are a Disability Confident Employer:Capgemini is proud to be a Disability Confident Employer (Level 2) under the UK Government's Disability Confident scheme. As part of our commitment to inclusive recruitment, we will offer an interview to all candidates who:Declare they have a disability, andMeet the minimum essential criteria for the role.Please opt in during the application process.Make It Real (what does it mean for you):You'd be joining an accredited Great Place to work for Wellbeing in 2024. Employee wellbeing is vitally important to us as an organisation. We see a healthy and happy workforce a critical component for us to achieve our organisational ambitions.To help support wellbeing we have trained 'Mental Health Champions' across each of our business areas, and we have invested in wellbeing apps such as Thrive and Peppy.You will be empowered to explore, innovate, and progress. You will benefit from Capgemini's 'learning for life' mindset, meaning you will have countless training and development opportunities from thinktanks to hackathons, and access to 250,000 courses with numerous external certifications from AWS, Microsoft, Harvard ManageMentor, Cybersecurity qualifications and much more.You will be joining one of the World's Most Ethical Companies, as recognised by Ethisphere for 13 consecutive years. We live our values by making ethical business choices every day. Working ethically is at the centre of our culture at Capgemini, meaning you will be helping to create a future we can all be proud of.Why you should consider Capgemini:Growing clients' businesses while building a more sustainable, more inclusive future is a tough ask. When you join Capgemini, you'll join a thriving company and become part of a collective of free-thinkers, entrepreneurs and industry experts. We find new ways technology can help us reimagine what's possible. It's why, together, we seek out opportunities that will transform the world's leading businesses, and it's how you'll gain the experiences and connections you need to shape your future. By learning from each other every day, sharing knowledge, and always pushing yourself to do better, you'll build the skills you want. You'll use your skills to help our clients leverage technology to innovate and grow their business. So, it might not always be easy, but making the world a better place rarely is.About Capgemini:Capgemini is an AI-powered global business and technology transformation partner, delivering tangible business value. We imagine the future of organizations and make it real with AI, technology and people. With our strong heritage of nearly 60 years, we are a responsible and diverse group of over 420,000 team members in more than 50 countries. We deliver end-to-end services and solutions with our deep industry expertise and strong partner ecosystem, leveraging our capabilities across strategy, technology, design, engineering and business operations. The Group reported 2025 global revenues of €22.5 billion.Make it real.
23/06/2026
Full time
Job Title: Data Architect - Azure Databricks / Azure Data Factory For London Market InsuranceExp Required - 10 years PlusLocation: LondonAbout the Job you are considering:We are looking for an experienced Data Architect with strong expertise in Azure Databricks, Azure Data Factory, Azure Data Lake, Delta Lake, data modelling, data governance, and cloud data architecture, along with domain experience in London Market Insurance.The candidate will be responsible for defining and delivering scalable data architecture solutions for insurance transformation programmes covering underwriting, claims, policy administration, bordereaux, delegated authority, premium processing, regulatory reporting, reinsurance, analytics, and data migration.The ideal candidate should have strong hands-on architecture experience in Azure-based data platforms and should be able to work closely with business stakeholders, enterprise architects, solution architects, data engineers, insurance SMEs, vendors, and delivery teamsHybrid working:The places that you work from day to day will vary according to your role, your needs, and those of the business; it will be a blend of Company offices, client sites, and your home; noting that you will be unable to work at home 100% of the time.Key Responsibilities:Define end-to-end data architecture for Azure-based data platforms using Azure Databricks, Azure Data Factory, ADLS Gen2, Delta Lake, Azure Synapse, and Power BI.Design scalable and secure lakehouse architecture using bronze, silver, and gold data layers.Lead architecture and design for data ingestion, transformation, curation, data marts, reporting, and analytics solutions.Create high-level and low-level data architecture documents, data flow diagrams, integration architecture, and data platform blueprints.Define architecture patterns for batch, incremental, real-time, and API-based data ingestion.Design reusable data ingestion and transformation frameworks using ADF and Databricks.Define data models for London Market Insurance data including policy, claims, premium, broker, bordereaux, delegated authority, reinsurance, exposure, and regulatory reporting data.Work with business analysts and insurance SMEs to understand London Market business processes and translate requirements into data architecture.Define standards for data modelling, source-to-target mapping, data quality, reconciliation, metadata, lineage, and auditability.Design data governance, security, access control, and compliance frameworks for insurance data.Support cloud migration, data warehouse modernisation, reporting transformation, and legacy system decommissioning initiatives.Review technical designs, data models, ETL/ELT pipelines, and engineering implementation.Provide architectural guidance to data engineers working on Azure Databricks, ADF, PySpark, SQL, and Delta Lake.Collaborate with enterprise architecture, solution architecture, security, infrastructure, DevOps, and business teams.Define CI/CD, DevOps, deployment, monitoring, and operational support architecture for data platforms.Identify performance, scalability, reliability, and cost optimisation opportunities across Azure data services.Support governance forums, architecture review boards, design authority meetings, and client stakeholder workshops.Mandatory SkillsStrong experience as a Data Architect or Senior Data Architect.Strong hands-on experience with Azure Databricks.Strong architecture and implementation experience with Azure Data Factory.Strong understanding of Azure Data Lake Storage Gen2.Strong experience with Delta Lake, lakehouse architecture, and medallion architecture.Excellent knowledge of data modelling, dimensional modelling, canonical data models, and enterprise data models.Strong experience in designing ETL/ELT data pipelines.Good understanding of PySpark, Spark SQL, Python, and SQL.Strong knowledge of data warehouse, data lake, data mart, and semantic layer architecture.Experience in defining data quality, data validation, reconciliation, audit, and exception handling frameworks.Experience with data governance, metadata management, data lineage, data catalogue, and data privacy controls.Experience with Azure security concepts including Managed Identity, Azure RBAC, Key Vault, ACLs, private endpoints, and encryption.Experience with CI/CD and DevOps practices using Azure DevOps, Git, ARM templates, Bicep, or Terraform.Strong stakeholder management, communication, presentation, and documentation skills.Ability to lead architecture discussions with business, technology, and senior client stakeholders.London Market Insurance Domain ExperienceThe candidate should have exposure to one or more of the following areas:Lloyd's Market operationsLondon Market Insurance operating modelSpecialty insurance and commercial insuranceBroker, carrier, managing agent, and syndicate data flowsUnderwriting data architectureClaims data architecturePolicy administration dataPremium and claims accountingBordereaux processingDelegated authority and binder dataCoverholder dataExposure managementReinsurance dataRegulatory and compliance reportingFinancial and management reportingBlueprint Two / London Market modernisation data initiativesAzure Architecture Skills ExpectedCandidate should have strong knowledge of the following Azure components:Azure DatabricksLakehouse architectureDatabricks notebooks, jobs, workflows, clustersDelta Lake optimisationUnity Catalog, if applicableDatabricks SQL, if applicableCluster sizing and cost optimisationSecurity and access control patternsAzure Data FactoryPipeline orchestrationLinked services and datasetsIntegration runtimeParameterised pipelinesTriggers and schedulingError handling and retry patternsMetadata-driven ingestion frameworksMonitoring and operational supportAzure Data Lake / StorageADLS Gen2 architectureLanding, raw, curated, and consumption zonesFolder hierarchy and naming standardsPartitioning strategyFile format standardsData retention and archival strategyAzure Governance and SecurityAzure Key VaultManaged IdentityAzure RBACStorage ACLsPrivate endpointsData maskingEncryption at rest and in transitLogging, monitoring, and audit controlsData Architecture ResponsibilitiesDefine conceptual, logical, and physical data models.Design canonical data models for insurance entities.Define data domains such as policy, claims, party, broker, premium, risk, exposure, and reinsurance.Define source-to-target mapping standards.Establish data quality rules and validation patterns.Define metadata and lineage requirements.Design reusable data ingestion frameworks.Define data retention, archival, and purge strategies.Define master and reference data management approach.Design reporting and analytics data marts.Define semantic layer and consumption patterns for BI tools.Review and approve data engineering designs and implementation.We are a Disability Confident Employer:Capgemini is proud to be a Disability Confident Employer (Level 2) under the UK Government's Disability Confident scheme. As part of our commitment to inclusive recruitment, we will offer an interview to all candidates who:Declare they have a disability, andMeet the minimum essential criteria for the role.Please opt in during the application process.Make It Real (what does it mean for you):You'd be joining an accredited Great Place to work for Wellbeing in 2024. Employee wellbeing is vitally important to us as an organisation. We see a healthy and happy workforce a critical component for us to achieve our organisational ambitions.To help support wellbeing we have trained 'Mental Health Champions' across each of our business areas, and we have invested in wellbeing apps such as Thrive and Peppy.You will be empowered to explore, innovate, and progress. You will benefit from Capgemini's 'learning for life' mindset, meaning you will have countless training and development opportunities from thinktanks to hackathons, and access to 250,000 courses with numerous external certifications from AWS, Microsoft, Harvard ManageMentor, Cybersecurity qualifications and much more.You will be joining one of the World's Most Ethical Companies, as recognised by Ethisphere for 13 consecutive years. We live our values by making ethical business choices every day. Working ethically is at the centre of our culture at Capgemini, meaning you will be helping to create a future we can all be proud of.Why you should consider Capgemini:Growing clients' businesses while building a more sustainable, more inclusive future is a tough ask. When you join Capgemini, you'll join a thriving company and become part of a collective of free-thinkers, entrepreneurs and industry experts. We find new ways technology can help us reimagine what's possible. It's why, together, we seek out opportunities that will transform the world's leading businesses, and it's how you'll gain the experiences and connections you need to shape your future. By learning from each other every day, sharing knowledge, and always pushing yourself to do better, you'll build the skills you want. You'll use your skills to help our clients leverage technology to innovate and grow their business. So, it might not always be easy, but making the world a better place rarely is.About Capgemini:Capgemini is an AI-powered global business and technology transformation partner, delivering tangible business value. We imagine the future of organizations and make it real with AI, technology and people. With our strong heritage of nearly 60 years, we are a responsible and diverse group of over 420,000 team members in more than 50 countries. We deliver end-to-end services and solutions with our deep industry expertise and strong partner ecosystem, leveraging our capabilities across strategy, technology, design, engineering and business operations. The Group reported 2025 global revenues of €22.5 billion.Make it real.
Locations 25 Bank Street, Canary Wharf, London, Greater London, E14 5JP, GB Job Schedule Full time Job Shift Day Job Description The Chief Data and Analytics Office (CDAO) builds enterprise-scale platforms for Data Management, Analytics, and AI/ML Operations used firm-wide across JPMorgan Chase. Within CDAO, the Data for AI Product Management team creates reusable platform solutions that transform how data producers and consumers discover, access, govern, and leverage data. As the Data Catalog Product Manager, you will play a pivotal role in building a unified, multi-channel data marketplace where thousands of firmwide datasets become easy to find, preview, and integrate across application and AI use cases. You will own the end-to-end vision, strategy, and execution - spanning a rich web UI, programmatic APIs, and future agentic integrations (Claude, Copilot, internal AI assistants) that meet consumers where they already work. We want someone who leads with problems, not solutions - who brings deep UX and service design expertise, has built catalog or marketplace products at scale, and can articulate how intelligent discovery evolves in an agentic AI world. What You'll Do Own the Catalog Vision & Strategy Define the multi-year product vision and roadmap for firmwide data discovery serving data scientists, ML engineers, analytics engineers, and increasingly business users. Establish north-star metrics tied to real impact: time-to-data, publishing velocity, discovery-to-integration conversion, repeat usage, and governance compliance . Own the full lifecycle from problem discovery delivery adoption iteration. Design a World-Class Discovery Experience Lead the UX and service design vision - intuitive, fast, and delightful across all touchpoints. Build rich dataset pages with metadata, schema previews, sample data, interactive code samples, lineage, quality scores, usage stats, ratings, and community annotations - inspired by the best consumer marketplace patterns (Kaggle, Spotify, App Store). Build for Multi-Channel: UI, API & Agents Architect an API-first platform powering a beautiful web UI today and programmatic access for code-first engineers. Meet consumers in their daily tools - notebooks, IDEs, orchestration platforms, chat interfaces, copilots - eliminating context-switching. Design composable, reusable solutions that integrate with the broader CDAO ecosystem. Champion Both Sides of the Marketplace Producers: Make it effortless to publish, document, version, and maintain datasets with rich metadata, automated quality profiling, and governance guardrails. Consumers: Reduce friction from discovery to access - self-service provisioning, entitlement workflows, one-click integration with SageMaker, Databricks, and EMR. Network effects: Analyze usage trends to improve data quality, discovery and relevancy across persona groups Collaborate with Engineering, Design & Data Science Work with UX designers and researchers on usability testing, rapid prototyping, and user validation. Write detailed PRDs and technical documentation that engineers and consumers can act on. Lead & Influence the team Influence cross-functional stakeholders - engineering, architecture, data science, governance, UX, and senior business leaders. Mentor and develop junior product managers. Required Skills 8+ years in technical product management delivering catalog, marketplace, or discovery platforms from ideation to production at scale. Deep UX & service design sensibility - passion to build clear, intuitive and scalable UI experiences. Multi-channel product delivery - shipped across web UI, API, and/or conversational/agent-based interfaces. Technical depth in data infrastructure - data catalogs, metadata management, governance frameworks, data quality tooling. Strong communication - translate technical complexity into clear narratives for engineers, designers, and executives. Prioritisation at scale - balance competing demands across a large stakeholder base by weighing business impact, user value, and technical feasibility. Preferred Experience in financial services or highly regulated industries . Built or scaled a data catalog, data marketplace, feature store, or developer portals (e.g., Kaggle Datasets, Unity Catalog, Collibra, Alation, Atlan). Understanding of agentic AI patterns - tool-use, RAG, function calling - and how marketplace APIs can be exposed to LLM-based agents. Experience with search relevance & recommendation systems - ranking algorithms, semantic search, personalisation. Hands-on with Snowflake, Databricks, Airflow, Kafka . Why Join Us Work on firm-wide platforms used by thousands of data scientists, ML engineers, and analysts across JPMC Shape the future of AI/ML and data infrastructure at one of the world's largest financial institutions About Us J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world's most prominent corporations, governments, wealthy individuals and institutional investors. Our first-class business in a first-class way approach to serving clients drives everything we do. We strive to build trusted, long-term partnerships to help our clients achieve their business objectives. We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit ourFAQs for more information about requesting an accommodation. About the Team Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we're setting our businesses, clients, customers and employees up for success.
23/06/2026
Full time
Locations 25 Bank Street, Canary Wharf, London, Greater London, E14 5JP, GB Job Schedule Full time Job Shift Day Job Description The Chief Data and Analytics Office (CDAO) builds enterprise-scale platforms for Data Management, Analytics, and AI/ML Operations used firm-wide across JPMorgan Chase. Within CDAO, the Data for AI Product Management team creates reusable platform solutions that transform how data producers and consumers discover, access, govern, and leverage data. As the Data Catalog Product Manager, you will play a pivotal role in building a unified, multi-channel data marketplace where thousands of firmwide datasets become easy to find, preview, and integrate across application and AI use cases. You will own the end-to-end vision, strategy, and execution - spanning a rich web UI, programmatic APIs, and future agentic integrations (Claude, Copilot, internal AI assistants) that meet consumers where they already work. We want someone who leads with problems, not solutions - who brings deep UX and service design expertise, has built catalog or marketplace products at scale, and can articulate how intelligent discovery evolves in an agentic AI world. What You'll Do Own the Catalog Vision & Strategy Define the multi-year product vision and roadmap for firmwide data discovery serving data scientists, ML engineers, analytics engineers, and increasingly business users. Establish north-star metrics tied to real impact: time-to-data, publishing velocity, discovery-to-integration conversion, repeat usage, and governance compliance . Own the full lifecycle from problem discovery delivery adoption iteration. Design a World-Class Discovery Experience Lead the UX and service design vision - intuitive, fast, and delightful across all touchpoints. Build rich dataset pages with metadata, schema previews, sample data, interactive code samples, lineage, quality scores, usage stats, ratings, and community annotations - inspired by the best consumer marketplace patterns (Kaggle, Spotify, App Store). Build for Multi-Channel: UI, API & Agents Architect an API-first platform powering a beautiful web UI today and programmatic access for code-first engineers. Meet consumers in their daily tools - notebooks, IDEs, orchestration platforms, chat interfaces, copilots - eliminating context-switching. Design composable, reusable solutions that integrate with the broader CDAO ecosystem. Champion Both Sides of the Marketplace Producers: Make it effortless to publish, document, version, and maintain datasets with rich metadata, automated quality profiling, and governance guardrails. Consumers: Reduce friction from discovery to access - self-service provisioning, entitlement workflows, one-click integration with SageMaker, Databricks, and EMR. Network effects: Analyze usage trends to improve data quality, discovery and relevancy across persona groups Collaborate with Engineering, Design & Data Science Work with UX designers and researchers on usability testing, rapid prototyping, and user validation. Write detailed PRDs and technical documentation that engineers and consumers can act on. Lead & Influence the team Influence cross-functional stakeholders - engineering, architecture, data science, governance, UX, and senior business leaders. Mentor and develop junior product managers. Required Skills 8+ years in technical product management delivering catalog, marketplace, or discovery platforms from ideation to production at scale. Deep UX & service design sensibility - passion to build clear, intuitive and scalable UI experiences. Multi-channel product delivery - shipped across web UI, API, and/or conversational/agent-based interfaces. Technical depth in data infrastructure - data catalogs, metadata management, governance frameworks, data quality tooling. Strong communication - translate technical complexity into clear narratives for engineers, designers, and executives. Prioritisation at scale - balance competing demands across a large stakeholder base by weighing business impact, user value, and technical feasibility. Preferred Experience in financial services or highly regulated industries . Built or scaled a data catalog, data marketplace, feature store, or developer portals (e.g., Kaggle Datasets, Unity Catalog, Collibra, Alation, Atlan). Understanding of agentic AI patterns - tool-use, RAG, function calling - and how marketplace APIs can be exposed to LLM-based agents. Experience with search relevance & recommendation systems - ranking algorithms, semantic search, personalisation. Hands-on with Snowflake, Databricks, Airflow, Kafka . Why Join Us Work on firm-wide platforms used by thousands of data scientists, ML engineers, and analysts across JPMC Shape the future of AI/ML and data infrastructure at one of the world's largest financial institutions About Us J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world's most prominent corporations, governments, wealthy individuals and institutional investors. Our first-class business in a first-class way approach to serving clients drives everything we do. We strive to build trusted, long-term partnerships to help our clients achieve their business objectives. We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit ourFAQs for more information about requesting an accommodation. About the Team Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we're setting our businesses, clients, customers and employees up for success.
About the Company A leading UK consulting and administration business specialising in pensions and insurance services. The organisation combines deep industry expertise with advanced technology and analytics to support large-scale pension schemes and their sponsoring employers. It provides administration for over one million members and delivers advisory services across schemes of all sizes, including many with assets exceeding £1bn. It also supports insurance clients in the life and bulk annuities sector. Package Details Remote (UK) | £45,000-£60,000 + 6% bonus Main Duties and Responsibilities Model Development (Azure Machine Learning Studio focus) Work collaboratively with actuarial and analytics teams to design, build, and deploy machine learning and statistical models using Azure Machine Learning Studio (AML Studio) in production environments. Apply appropriate ML techniques to improve predictions such as longevity, default risk, and investment outcomes. Machine Learning Operations (MLOps in Azure) Manage the full ML life cycle using Azure ML Studio, including deployment, monitoring, retraining pipelines, and version control. Implement robust MLOps practices such as model drift detection, data quality monitoring, and automated retraining workflows. Data Engineering and Preprocessing Develop and maintain scalable data pipelines using Python, SQL, and Azure Data Factory (ADF). Ensure data is clean, reliable, and structured for use in Azure ML Studio workflows. Software Development Produce clean, efficient, and production-grade Python code. Apply CI/CD practices and DevOps/MLOps principles integrated with Azure Machine Learning Studio environments. Cross-functional Collaboration Work closely with actuarial analysts and modelling teams to translate outputs from Azure ML Studio into actionable insights and business recommendations. Innovation and Continuous Improvement Stay up to date with developments in Azure Machine Learning Studio, MLOps, and data science technologies, identifying opportunities to improve models, automation, and delivery efficiency. Training and Knowledge Sharing Support and train team members on machine learning approaches and Azure ML Studio workflows, including deployment and monitoring practices. Stakeholder Communication Clearly explain machine learning concepts and Azure ML Studio-based solutions to both technical and non-technical stakeholders. Job Requirements Essential Strong hands-on experience with Azure Machine Learning Studio (AML Studio), including end-to-end model development, deployment, monitoring, and life cycle management in production environments Experience building and optimising ML models using Azure ML workflows Strong Python and SQL skills for data manipulation, modelling, and automation Experience with Azure Data Factory (ADF) for data pipeline development Strong understanding of CI/CD and MLOps practices, ideally within Azure environments Experience with data visualisation tools such as Power BI Strong communication skills with ability to explain technical concepts clearly to non-technical audiences Desirable Experience in pensions, insurance, or regulated financial services Experience working in multidisciplinary analytics or actuarial teams Broader exposure to Azure ecosystem tools (eg, Azure DevOps, Databricks) Key Requirement The most critical requirement for this role is hands-on, production-level experience with Azure Machine Learning Studio (AML Studio), including building and deploying ML models end-to-end, managing model life cycle in production, implementing MLOps workflows (monitoring, drift detection, retraining), and integrating Azure ML Studio with data pipelines and CI/CD processes. Due to the volume of applications received for positions, it will not be possible to respond to all applications and only applicants who are considered suitable for interview will be contacted. Proactive Appointments Limited operates as an employment agency and employment business and is an equal opportunities organisation We take our obligations to protect your personal data very seriously. Any information provided to us will be processed as detailed in our Privacy Notice, a copy of which can be found on our website
22/06/2026
Full time
About the Company A leading UK consulting and administration business specialising in pensions and insurance services. The organisation combines deep industry expertise with advanced technology and analytics to support large-scale pension schemes and their sponsoring employers. It provides administration for over one million members and delivers advisory services across schemes of all sizes, including many with assets exceeding £1bn. It also supports insurance clients in the life and bulk annuities sector. Package Details Remote (UK) | £45,000-£60,000 + 6% bonus Main Duties and Responsibilities Model Development (Azure Machine Learning Studio focus) Work collaboratively with actuarial and analytics teams to design, build, and deploy machine learning and statistical models using Azure Machine Learning Studio (AML Studio) in production environments. Apply appropriate ML techniques to improve predictions such as longevity, default risk, and investment outcomes. Machine Learning Operations (MLOps in Azure) Manage the full ML life cycle using Azure ML Studio, including deployment, monitoring, retraining pipelines, and version control. Implement robust MLOps practices such as model drift detection, data quality monitoring, and automated retraining workflows. Data Engineering and Preprocessing Develop and maintain scalable data pipelines using Python, SQL, and Azure Data Factory (ADF). Ensure data is clean, reliable, and structured for use in Azure ML Studio workflows. Software Development Produce clean, efficient, and production-grade Python code. Apply CI/CD practices and DevOps/MLOps principles integrated with Azure Machine Learning Studio environments. Cross-functional Collaboration Work closely with actuarial analysts and modelling teams to translate outputs from Azure ML Studio into actionable insights and business recommendations. Innovation and Continuous Improvement Stay up to date with developments in Azure Machine Learning Studio, MLOps, and data science technologies, identifying opportunities to improve models, automation, and delivery efficiency. Training and Knowledge Sharing Support and train team members on machine learning approaches and Azure ML Studio workflows, including deployment and monitoring practices. Stakeholder Communication Clearly explain machine learning concepts and Azure ML Studio-based solutions to both technical and non-technical stakeholders. Job Requirements Essential Strong hands-on experience with Azure Machine Learning Studio (AML Studio), including end-to-end model development, deployment, monitoring, and life cycle management in production environments Experience building and optimising ML models using Azure ML workflows Strong Python and SQL skills for data manipulation, modelling, and automation Experience with Azure Data Factory (ADF) for data pipeline development Strong understanding of CI/CD and MLOps practices, ideally within Azure environments Experience with data visualisation tools such as Power BI Strong communication skills with ability to explain technical concepts clearly to non-technical audiences Desirable Experience in pensions, insurance, or regulated financial services Experience working in multidisciplinary analytics or actuarial teams Broader exposure to Azure ecosystem tools (eg, Azure DevOps, Databricks) Key Requirement The most critical requirement for this role is hands-on, production-level experience with Azure Machine Learning Studio (AML Studio), including building and deploying ML models end-to-end, managing model life cycle in production, implementing MLOps workflows (monitoring, drift detection, retraining), and integrating Azure ML Studio with data pipelines and CI/CD processes. Due to the volume of applications received for positions, it will not be possible to respond to all applications and only applicants who are considered suitable for interview will be contacted. Proactive Appointments Limited operates as an employment agency and employment business and is an equal opportunities organisation We take our obligations to protect your personal data very seriously. Any information provided to us will be processed as detailed in our Privacy Notice, a copy of which can be found on our website
Pantheon has been at the forefront of private markets investing for more than 40 years, earning a reputation for an innovative approach to investing in secondaries, co investments, and primary fund investments, as well as capital formation across commingled funds, evergreen vehicles and customized solutions. Our specialist investment capabilities span multiple strategies across private equity, infrastructure and real assets, and private credit. Through our collaborative and committed culture, we find new ways to solve complex problems together and deliver innovative investment opportunities across private markets. Pantheon currently manages approximately $82.3 billion in AUM across all its strategies, serving more than 750 institutional and 638 private wealth clients worldwide. Pantheon is in the process of building a cloud native, AI ready Data Platform based on the Databricks Lakehouse architecture, enabling analytics, operational use cases, and advanced ML/AI workloads. We require an experienced and passionate hands on Senior Data Engineer to design and implement new data pipelines for adaptation to business and/or technology changes. This role will be integral to the success of this program and establishing Pantheon as a data centric organisation. You will be working with a modern Azure tech stack and proven experience of ingesting and transforming data from a variety of internal and external systems is core to the role. You will be part of a small and highly skilled team, and you will need to be passionate about providing best in class solutions to our global user base. Key Responsibilities Design, build, and maintain scalable, secure, and high performance data pipelines on Azure, primarily using Azure Databricks, Azure Data Factory, and Azure Functions. Develop and optimise batch and streaming data processing solutions using PySpark and SQL to support analytics, reporting, and downstream data products. Implement robust data transformation layers using dbt, ensuring well structured, tested, and documented analytical models. Collaborate closely with business analysts, QA teams, and business stakeholders to translate data requirements into reliable technical solutions. Ensure data quality, reliability, and observability through automated testing, monitoring, logging, and alerting. Lead on performance tuning, cost optimisation, and capacity planning across Databricks and associated Azure services. Implement and maintain CI/CD pipelines using Azure DevOps, promoting best practices for version control, automated testing, and deployment. Enforce data governance, security, and compliance standards, including access controls, data lineage, and auditability. Contribute to architectural decisions and provide technical leadership, mentoring junior engineers and setting engineering standards. Produce clear technical documentation and contribute to knowledge sharing across the data engineering function. Knowledge & Experience Required Essential Technical Skills Python and PySpark for large-scale data processing. SQL (advanced querying, optimisation, and data modelling). Azure Data Factory (pipeline orchestration and integration). Azure DevOps (Git, CI/CD pipelines, release management). Lakehouse architecture (Databricks Unity Catalog, Delta Lake optimisation techniques such as Z ordering, liquid clustering). Data modelling (star schemas, data vault, or lakehouse aligned approaches). Data quality, testing frameworks, and monitoring/observability. Strong problem solving ability and a pragmatic, engineering led mindset. Experience in Agile SW development environment. Excellent communication skills, with the ability to explain complex technical concepts to both technical and non technical stakeholders. Leadership and mentoring capability, with a focus on raising engineering standards and best practices. Significant commercial experience (typically 5+ years) in data engineering roles, with demonstrable experience designing and operating production grade data platforms. Strong hands on experience with Azure Databricks, including cluster configuration, job orchestration, and performance optimisation. Proven experience building data pipelines with Databricks and Azure Data Factory; integrating with Azure native services (e.g. Data Lake Storage Gen2, Azure Functions). Advanced experience with Python for data engineering, including PySpark for distributed data processing. Strong SQL expertise, with experience designing and optimising complex analytical queries and data models. Practical experience using dbt in a production environment, including model design, testing, documentation, and deployment. Experience implementing CI/CD pipelines using Azure DevOps or equivalent tooling. Data as a Product mindset. AI / ML / GenAI Enablement Enable ML/AI workloads on the Databricks data platform. Collaborate with AI Product Team to deliver use cases. Enable RAG pipelines / vector storage patterns to support AI products. Desired Experience Financial services industry or private market experience. Development with coding agents (e.g., Anthropic Claude Code, OpenAI Codex, etc). This job description is not to be construed as an exhaustive statement of duties, responsibilities, or requirements. You may be required to perform other job-related duties as reasonably requested by your manager. Pantheon is an Equal Opportunities employer. We are committed to building a diverse and inclusive workforce so if you're excited about this role but your past experience doesn't perfectly align we'd still encourage you to apply. We are committed to ensuring that all candidates have an equal opportunity to participate in the recruitment process. If you require any reasonable adjustments to accommodate your needs, please use this space to describe the nature of the adjustments you require.
22/06/2026
Full time
Pantheon has been at the forefront of private markets investing for more than 40 years, earning a reputation for an innovative approach to investing in secondaries, co investments, and primary fund investments, as well as capital formation across commingled funds, evergreen vehicles and customized solutions. Our specialist investment capabilities span multiple strategies across private equity, infrastructure and real assets, and private credit. Through our collaborative and committed culture, we find new ways to solve complex problems together and deliver innovative investment opportunities across private markets. Pantheon currently manages approximately $82.3 billion in AUM across all its strategies, serving more than 750 institutional and 638 private wealth clients worldwide. Pantheon is in the process of building a cloud native, AI ready Data Platform based on the Databricks Lakehouse architecture, enabling analytics, operational use cases, and advanced ML/AI workloads. We require an experienced and passionate hands on Senior Data Engineer to design and implement new data pipelines for adaptation to business and/or technology changes. This role will be integral to the success of this program and establishing Pantheon as a data centric organisation. You will be working with a modern Azure tech stack and proven experience of ingesting and transforming data from a variety of internal and external systems is core to the role. You will be part of a small and highly skilled team, and you will need to be passionate about providing best in class solutions to our global user base. Key Responsibilities Design, build, and maintain scalable, secure, and high performance data pipelines on Azure, primarily using Azure Databricks, Azure Data Factory, and Azure Functions. Develop and optimise batch and streaming data processing solutions using PySpark and SQL to support analytics, reporting, and downstream data products. Implement robust data transformation layers using dbt, ensuring well structured, tested, and documented analytical models. Collaborate closely with business analysts, QA teams, and business stakeholders to translate data requirements into reliable technical solutions. Ensure data quality, reliability, and observability through automated testing, monitoring, logging, and alerting. Lead on performance tuning, cost optimisation, and capacity planning across Databricks and associated Azure services. Implement and maintain CI/CD pipelines using Azure DevOps, promoting best practices for version control, automated testing, and deployment. Enforce data governance, security, and compliance standards, including access controls, data lineage, and auditability. Contribute to architectural decisions and provide technical leadership, mentoring junior engineers and setting engineering standards. Produce clear technical documentation and contribute to knowledge sharing across the data engineering function. Knowledge & Experience Required Essential Technical Skills Python and PySpark for large-scale data processing. SQL (advanced querying, optimisation, and data modelling). Azure Data Factory (pipeline orchestration and integration). Azure DevOps (Git, CI/CD pipelines, release management). Lakehouse architecture (Databricks Unity Catalog, Delta Lake optimisation techniques such as Z ordering, liquid clustering). Data modelling (star schemas, data vault, or lakehouse aligned approaches). Data quality, testing frameworks, and monitoring/observability. Strong problem solving ability and a pragmatic, engineering led mindset. Experience in Agile SW development environment. Excellent communication skills, with the ability to explain complex technical concepts to both technical and non technical stakeholders. Leadership and mentoring capability, with a focus on raising engineering standards and best practices. Significant commercial experience (typically 5+ years) in data engineering roles, with demonstrable experience designing and operating production grade data platforms. Strong hands on experience with Azure Databricks, including cluster configuration, job orchestration, and performance optimisation. Proven experience building data pipelines with Databricks and Azure Data Factory; integrating with Azure native services (e.g. Data Lake Storage Gen2, Azure Functions). Advanced experience with Python for data engineering, including PySpark for distributed data processing. Strong SQL expertise, with experience designing and optimising complex analytical queries and data models. Practical experience using dbt in a production environment, including model design, testing, documentation, and deployment. Experience implementing CI/CD pipelines using Azure DevOps or equivalent tooling. Data as a Product mindset. AI / ML / GenAI Enablement Enable ML/AI workloads on the Databricks data platform. Collaborate with AI Product Team to deliver use cases. Enable RAG pipelines / vector storage patterns to support AI products. Desired Experience Financial services industry or private market experience. Development with coding agents (e.g., Anthropic Claude Code, OpenAI Codex, etc). This job description is not to be construed as an exhaustive statement of duties, responsibilities, or requirements. You may be required to perform other job-related duties as reasonably requested by your manager. Pantheon is an Equal Opportunities employer. We are committed to building a diverse and inclusive workforce so if you're excited about this role but your past experience doesn't perfectly align we'd still encourage you to apply. We are committed to ensuring that all candidates have an equal opportunity to participate in the recruitment process. If you require any reasonable adjustments to accommodate your needs, please use this space to describe the nature of the adjustments you require.
Do you want to boost your career and collaborate with expert, talented colleagues to solve and deliver against our clients' most important challenges? We are growing and are looking for people to join our team. You'll be part of an entrepreneurial, high-growth environment of 300,000 employees. Our dynamic organization allows you to work across functional business pillars, contributing your ideas, experiences, diverse thinking, and a strong mindset. Are you ready? About your role Enterprise AI is forcing organisations to rethink their data estates. Data platforms designed mainly for reporting are often not enough for GenAI, semantic search, agentic workflows and AI-enabled decision making. Clients now need data that is trusted, governed, contextualised and consumable by both people and intelligent systems. We are looking for client-facing Enterprise Data Architects to join our growing Enterprise AI practice. You will help clients transform fragmented data estates into AI ready foundations, advising on architecture decisions across cloud data platforms, lakehouse and warehouse patterns, data products, semantic layers, metadata, lineage, governance, knowledge graphs and GenAI retrieval patterns. This is a consulting role, not a purely internal architecture role. You will diagnose ambiguous client problems, shape options, make trade offs explicit, and translate complex data architecture issues into clear decisions for both technical teams and executive stakeholders. You will work in cross functional teams alongside product owners, data scientists, ML and GenAI engineers, data engineers, business analysts and client stakeholders. Typical outputs may include target state architectures, maturity assessments, platform option appraisals, data product designs, governance models, lineage maps, ontology and semantic models, integration patterns, GenAI data readiness assessments and implementation roadmaps. We are hiring across several levels. At earlier levels, we expect strong architecture delivery experience and hands on platform understanding. At senior levels, we expect the ability to shape enterprise data strategy, influence senior stakeholders, lead complex architecture decisions and guide multi disciplinary delivery teams. We do not expect every candidate to be a specialist in every aspect of AI ready data architecture. We are looking for architects with strong core data architecture experience and credible depth in some of the areas that matter for AI enabled data estates, such as governance, semantic modelling, lakehouse architecture, data products, metadata management, knowledge graphs, RAG or enterprise data strategy. Responsibilities Design AI ready enterprise data architectures that enable analytics, AI, ML, GenAI and agentic applications to consume data accurately, securely and with appropriate business context. Assess clients' existing data estates, diagnose structural, governance, semantic and quality issues, and design pragmatic modernisation roadmaps. Advise clients on architecture and platform choices, helping them navigate trade offs between lakehouses, warehouses, data fabrics, graph databases, semantic layers, vector search and hybrid architectures. Define data governance and metadata patterns covering ownership, stewardship, quality, lineage, cataloguing, access control and data lifecycle management. Design data products, data contracts and information models that make enterprise data reusable across analytics, AI, GenAI and operational workflows. Shape semantic layers, ontologies and knowledge graph patterns where these improve data discoverability, interoperability, explainability or AI consumption. Oversee high level design of ingestion, integration and transformation patterns, including batch, event driven and real time architectures. Identify and mitigate data related risks, including poor data quality, weak provenance, data leakage, inappropriate access, retrieval failure and inference time use of enterprise knowledge. Act as a trusted advisor to client stakeholders, translating technical architecture concepts into clear business outcomes, options and risks. Contribute to proposals, client conversations, internal methods and thought leadership on enterprise data architecture and AI ready data foundations. Skills and Qualifications Essential Skills 5-10+ years, depending on level, in data architecture, enterprise architecture, solution architecture or senior data engineering roles. Demonstrable experience designing modern data architectures for analytics, AI, ML or GenAI consumption. Strong understanding of enterprise data architecture patterns, including cloud data platforms, lakehouses, warehouses, data integration, data modelling and metadata management. Experience contributing to or leading data governance initiatives, including catalogues, lineage, ownership, stewardship, data quality and metadata management. Practical understanding of semantic layers, ontologies or knowledge graph concepts, with hands on experience in at least one of these areas. Deep experience with at least one major cloud data platform, such as AWS, Azure or Google Cloud, and familiarity with leading lakehouse or warehouse technologies. Understanding of how data architecture decisions affect AI and GenAI outcomes, including data quality, provenance, context, retrieval, security, privacy and semantic consistency. Familiarity with GenAI data patterns such as retrieval augmented generation, vector search, embedding pipelines, chunking strategies or enterprise search. Strong stakeholder management and communication skills, with the ability to present complex technical trade offs clearly to non technical sponsors and senior executives. Excellent written and verbal communication skills in English. Bachelor's degree or equivalent experience; quantitative, technical or analytical disciplines are an advantage. Willingness to travel, up to around 60% depending on project requirements, across the UK and internationally. Preferred Skills A second major European language is an advantage. Experience with graph modelling, ontology standards or graph query languages such as RDF, OWL and SPARQL. Familiarity with feature store design and MLOps / DataOps pipeline integration. Experience with stream processing at scale using Apache Kafka or Apache Flink. Background in master data management or data mesh architecture. Consulting or comparable client facing delivery experience. Exposure to cloud data platforms (Databricks, Snowflake, Microsoft Fabric, Azure Synapse, Google BigQuery, Amazon Redshift), data engineering and orchestration (Spark, dbt, Airflow, Azure Data Factory, AWS Glue, Dataflow, Kafka, Flink), governance, catalogue and lineage tools (Microsoft Purview, Collibra, Informatica, Alation, Atlan, OpenLineage), graph, ontology and semantic technologies (Neo4j, Amazon Neptune, Stardog, GraphDB, RDF, OWL, SPARQL), or AI/ML data infrastructure (vector databases such as Pinecone, Weaviate, Milvus, Azure AI Search, OpenSearch or pgvector; feature stores such as Feast or Tecton; model lifecycle and experiment tracking tools such as MLflow). We do not expect candidates to have worked with all of them. Personal Attributes Comfortable working in ambiguous consulting environments, shaping options, making trade offs explicit and taking senior stakeholders on the journey from strategy to implementation. Self directed, able to prioritise and juggle multiple workstreams. Clear communicator who can simplify complexity for technical and non technical audiences alike. Collaborative, curious, continuous learner. We offer industry leading compensation and benefits, along with top training and development opportunities so that you can grow your career and achieve your personal ambitions.
22/06/2026
Full time
Do you want to boost your career and collaborate with expert, talented colleagues to solve and deliver against our clients' most important challenges? We are growing and are looking for people to join our team. You'll be part of an entrepreneurial, high-growth environment of 300,000 employees. Our dynamic organization allows you to work across functional business pillars, contributing your ideas, experiences, diverse thinking, and a strong mindset. Are you ready? About your role Enterprise AI is forcing organisations to rethink their data estates. Data platforms designed mainly for reporting are often not enough for GenAI, semantic search, agentic workflows and AI-enabled decision making. Clients now need data that is trusted, governed, contextualised and consumable by both people and intelligent systems. We are looking for client-facing Enterprise Data Architects to join our growing Enterprise AI practice. You will help clients transform fragmented data estates into AI ready foundations, advising on architecture decisions across cloud data platforms, lakehouse and warehouse patterns, data products, semantic layers, metadata, lineage, governance, knowledge graphs and GenAI retrieval patterns. This is a consulting role, not a purely internal architecture role. You will diagnose ambiguous client problems, shape options, make trade offs explicit, and translate complex data architecture issues into clear decisions for both technical teams and executive stakeholders. You will work in cross functional teams alongside product owners, data scientists, ML and GenAI engineers, data engineers, business analysts and client stakeholders. Typical outputs may include target state architectures, maturity assessments, platform option appraisals, data product designs, governance models, lineage maps, ontology and semantic models, integration patterns, GenAI data readiness assessments and implementation roadmaps. We are hiring across several levels. At earlier levels, we expect strong architecture delivery experience and hands on platform understanding. At senior levels, we expect the ability to shape enterprise data strategy, influence senior stakeholders, lead complex architecture decisions and guide multi disciplinary delivery teams. We do not expect every candidate to be a specialist in every aspect of AI ready data architecture. We are looking for architects with strong core data architecture experience and credible depth in some of the areas that matter for AI enabled data estates, such as governance, semantic modelling, lakehouse architecture, data products, metadata management, knowledge graphs, RAG or enterprise data strategy. Responsibilities Design AI ready enterprise data architectures that enable analytics, AI, ML, GenAI and agentic applications to consume data accurately, securely and with appropriate business context. Assess clients' existing data estates, diagnose structural, governance, semantic and quality issues, and design pragmatic modernisation roadmaps. Advise clients on architecture and platform choices, helping them navigate trade offs between lakehouses, warehouses, data fabrics, graph databases, semantic layers, vector search and hybrid architectures. Define data governance and metadata patterns covering ownership, stewardship, quality, lineage, cataloguing, access control and data lifecycle management. Design data products, data contracts and information models that make enterprise data reusable across analytics, AI, GenAI and operational workflows. Shape semantic layers, ontologies and knowledge graph patterns where these improve data discoverability, interoperability, explainability or AI consumption. Oversee high level design of ingestion, integration and transformation patterns, including batch, event driven and real time architectures. Identify and mitigate data related risks, including poor data quality, weak provenance, data leakage, inappropriate access, retrieval failure and inference time use of enterprise knowledge. Act as a trusted advisor to client stakeholders, translating technical architecture concepts into clear business outcomes, options and risks. Contribute to proposals, client conversations, internal methods and thought leadership on enterprise data architecture and AI ready data foundations. Skills and Qualifications Essential Skills 5-10+ years, depending on level, in data architecture, enterprise architecture, solution architecture or senior data engineering roles. Demonstrable experience designing modern data architectures for analytics, AI, ML or GenAI consumption. Strong understanding of enterprise data architecture patterns, including cloud data platforms, lakehouses, warehouses, data integration, data modelling and metadata management. Experience contributing to or leading data governance initiatives, including catalogues, lineage, ownership, stewardship, data quality and metadata management. Practical understanding of semantic layers, ontologies or knowledge graph concepts, with hands on experience in at least one of these areas. Deep experience with at least one major cloud data platform, such as AWS, Azure or Google Cloud, and familiarity with leading lakehouse or warehouse technologies. Understanding of how data architecture decisions affect AI and GenAI outcomes, including data quality, provenance, context, retrieval, security, privacy and semantic consistency. Familiarity with GenAI data patterns such as retrieval augmented generation, vector search, embedding pipelines, chunking strategies or enterprise search. Strong stakeholder management and communication skills, with the ability to present complex technical trade offs clearly to non technical sponsors and senior executives. Excellent written and verbal communication skills in English. Bachelor's degree or equivalent experience; quantitative, technical or analytical disciplines are an advantage. Willingness to travel, up to around 60% depending on project requirements, across the UK and internationally. Preferred Skills A second major European language is an advantage. Experience with graph modelling, ontology standards or graph query languages such as RDF, OWL and SPARQL. Familiarity with feature store design and MLOps / DataOps pipeline integration. Experience with stream processing at scale using Apache Kafka or Apache Flink. Background in master data management or data mesh architecture. Consulting or comparable client facing delivery experience. Exposure to cloud data platforms (Databricks, Snowflake, Microsoft Fabric, Azure Synapse, Google BigQuery, Amazon Redshift), data engineering and orchestration (Spark, dbt, Airflow, Azure Data Factory, AWS Glue, Dataflow, Kafka, Flink), governance, catalogue and lineage tools (Microsoft Purview, Collibra, Informatica, Alation, Atlan, OpenLineage), graph, ontology and semantic technologies (Neo4j, Amazon Neptune, Stardog, GraphDB, RDF, OWL, SPARQL), or AI/ML data infrastructure (vector databases such as Pinecone, Weaviate, Milvus, Azure AI Search, OpenSearch or pgvector; feature stores such as Feast or Tecton; model lifecycle and experiment tracking tools such as MLflow). We do not expect candidates to have worked with all of them. Personal Attributes Comfortable working in ambiguous consulting environments, shaping options, making trade offs explicit and taking senior stakeholders on the journey from strategy to implementation. Self directed, able to prioritise and juggle multiple workstreams. Clear communicator who can simplify complexity for technical and non technical audiences alike. Collaborative, curious, continuous learner. We offer industry leading compensation and benefits, along with top training and development opportunities so that you can grow your career and achieve your personal ambitions.
Business Analyst - Basel III Endgame / SA CCR page is loaded Business Analyst - Basel III Endgame / SA CCRremote type: Hybridlocations: Belfast - 20 Adelaide Streetposted on: Posted Todayjob requisition id: JR-Huron is redefining what a global consulting organization can be. Advancing new ideas every day to build even stronger clients, individuals and communities. We're helping our clients find new ways to drive growth, enhance business performance and sustain leadership in the markets they serve. And, we're developing strategies and implementing solutions that enable the transformative change they need to own their future. As a member of the Huron corporate team, you'll help to evolve our business model to stay ahead of market forces, industry trends and client needs. Our accounting, finance, human resources, IT, legal, marketing and facilities management professionals work collaboratively to support Huron's collective strategies and enable real transformation to produce sustainable business results. Join our team and create your future. We are seeking a highly skilled Business Analyst with deep expertise in Basel III Endgame and SA CCR to support regulatory transformation across risk, capital and liquidity frameworks. You will analyse requirements, map data lineage, evaluate capital impacts and design robust regulatory workflows that withstand audit and supervisory scrutiny. This role requires strong analytical depth, regulatory fluency, and the ability to convert technical models into actionable insights for risk, finance and senior leadership. Your Role: A Regulatory Analyst Advancing SA CCR Transformation Interpret Basel III Endgame & SA CCR requirements , translating RC, PFE, multipliers and EAD rules into structured business and functional requirements. Link capital outcomes to financial metrics , connecting RWA changes to ROE, liquidity usage and CFO level performance indicators, including capital release quantification. Perform in depth data analysis , mapping data lineage, identifying golden sources and assessing data completeness across OTC derivatives, SFTs, collateral and market data feeds. Design compliant and repeatable workflows , establishing traceable processes with embedded governance, auditability and regulatory control points. Conduct scenario analysis and stress testing , including CSA modifications, MPOR adjustments, volatility shocks and what if modelling for exposure and capital sensitivity. Assess SA CCR interaction with liquidity , analysing how derivatives exposures drive collateral, funding, LCR consumption and liquidity capital interdependencies. Apply AI enabled regulatory interpretation , using NLP/LLM tools to parse regulatory text, generate requirement traceability matrices and highlight rule deltas between CEM and SA CCR. Identify data quality gaps via ML assisted techniques , detecting missing or inconsistent attributes (netting, CSA, MPOR, collateral), and uncovering capital leakage caused by poor mappings. Support AI accelerated data discovery , applying pattern detection and profiling to reconcile capital efficiency with liquidity resilience. Collaborate with stakeholders , engaging Risk, Treasury, CRO functions, Risk IT and trading teams to communicate findings, resolve issues and shape regulatory solutions. The Profile We're Looking For: A Regulatory Minded Business Analyst Strong regulatory expertise , with hands on experience interpreting Basel III Endgame, SA CCR exposure methodology and regulatory reporting formats (e.g., COREP, FR Y 14/Q). Capital optimisation knowledge , including how RWA changes impact ROE, balance sheet usage, liquidity consumption and senior leadership metrics. Advanced data analysis capability , with experience in lineage mapping, golden source assessment and evaluating data quality across derivatives, SFTs and collateral. Process design & governance experience , capable of defining controlled, auditable and regulator aligned workflows across risk and capital functions. Stakeholder management skills , with the ability to translate technical content into business impacts for CRO, Treasury, Finance, Risk IT and Front Office audiences. Scenario & stress testing familiarity , including modelling CSA changes, MPOR scenarios, sensitivity analysis and exposure recalculation effects. AI assisted regulatory analysis experience , including NLP/LLM tools for requirement mapping, automated RTMs and interpretation comparisons. Data quality diagnostics using ML , able to identify hidden inconsistencies and capital inefficiencies using advanced pattern detection. Good to have: familiarity with Databricks Data Quality frameworks, including AI based pattern identification. Professional characteristics: analytical, structured, curious and able to operate independently in fast paced regulatory programmes. Equal Opportunity & Compliance Huron is an equal opportunity employer. We are committed to creating an inclusive and diverse workplace. All employment decisions are made without regard to race, colour, religion, gender, sexual orientation, gender identity or expression, national origin, age, disability, or any other legally protected status. Position Level Senior Associate Country United KingdomAt Huron, we're redefining what a consulting organization can be. We go beyond advice to deliver results that last. We inherit our client's challenges as if they were our own. We help them transform for the future. We advocate. We make a difference. And we intelligently, passionately, relentlessly do great work together. Whether you have years of experience or come right out of college, we invite you to explore our many opportunities. Find out how you can use your talents and develop your skills to make an impact immediately. Learn about how our culture and values provide you with the kind of environment that invites new ideas and innovation. Come see how we collaborate with each other in a culture of learning, coaching, diversity and inclusion. And hear about our unwavering commitment to make a difference in partnership with our clients, shareholders, communities and colleagues. Huron Consulting Group offers a competitive compensation and benefits package including medical, dental, and vision coverage to employees and dependents; a 401(k) plan with a generous employer match; an employee stock purchase plan; a generous Paid Time Off policy; and paid parental leave and adoption assistance. Our Wellness Program supports employee total well-being by providing free annual health screenings and coaching, bank at work, and on-site workshops, as well as ongoing programs recognizing major events in the lives of our employees throughout the year. All benefits and programs are subject to applicable eligibility requirements. Huron is fully committed to providing equal employment opportunity to job applicants and employees in recruitment, hiring, employment, compensation, benefits, promotions, transfers, training, and all other terms and conditions of employment. Huron will not discriminate on the basis of age, race, color, gender, marital status, sexual orientation, gender identity, pregnancy, national origin, religion, veteran status, physical or mental disability, genetic information, creed, citizenship or any other status protected by laws or regulations in the locations where we do business. We endeavor to maintain a drug-free workplace.
22/06/2026
Full time
Business Analyst - Basel III Endgame / SA CCR page is loaded Business Analyst - Basel III Endgame / SA CCRremote type: Hybridlocations: Belfast - 20 Adelaide Streetposted on: Posted Todayjob requisition id: JR-Huron is redefining what a global consulting organization can be. Advancing new ideas every day to build even stronger clients, individuals and communities. We're helping our clients find new ways to drive growth, enhance business performance and sustain leadership in the markets they serve. And, we're developing strategies and implementing solutions that enable the transformative change they need to own their future. As a member of the Huron corporate team, you'll help to evolve our business model to stay ahead of market forces, industry trends and client needs. Our accounting, finance, human resources, IT, legal, marketing and facilities management professionals work collaboratively to support Huron's collective strategies and enable real transformation to produce sustainable business results. Join our team and create your future. We are seeking a highly skilled Business Analyst with deep expertise in Basel III Endgame and SA CCR to support regulatory transformation across risk, capital and liquidity frameworks. You will analyse requirements, map data lineage, evaluate capital impacts and design robust regulatory workflows that withstand audit and supervisory scrutiny. This role requires strong analytical depth, regulatory fluency, and the ability to convert technical models into actionable insights for risk, finance and senior leadership. Your Role: A Regulatory Analyst Advancing SA CCR Transformation Interpret Basel III Endgame & SA CCR requirements , translating RC, PFE, multipliers and EAD rules into structured business and functional requirements. Link capital outcomes to financial metrics , connecting RWA changes to ROE, liquidity usage and CFO level performance indicators, including capital release quantification. Perform in depth data analysis , mapping data lineage, identifying golden sources and assessing data completeness across OTC derivatives, SFTs, collateral and market data feeds. Design compliant and repeatable workflows , establishing traceable processes with embedded governance, auditability and regulatory control points. Conduct scenario analysis and stress testing , including CSA modifications, MPOR adjustments, volatility shocks and what if modelling for exposure and capital sensitivity. Assess SA CCR interaction with liquidity , analysing how derivatives exposures drive collateral, funding, LCR consumption and liquidity capital interdependencies. Apply AI enabled regulatory interpretation , using NLP/LLM tools to parse regulatory text, generate requirement traceability matrices and highlight rule deltas between CEM and SA CCR. Identify data quality gaps via ML assisted techniques , detecting missing or inconsistent attributes (netting, CSA, MPOR, collateral), and uncovering capital leakage caused by poor mappings. Support AI accelerated data discovery , applying pattern detection and profiling to reconcile capital efficiency with liquidity resilience. Collaborate with stakeholders , engaging Risk, Treasury, CRO functions, Risk IT and trading teams to communicate findings, resolve issues and shape regulatory solutions. The Profile We're Looking For: A Regulatory Minded Business Analyst Strong regulatory expertise , with hands on experience interpreting Basel III Endgame, SA CCR exposure methodology and regulatory reporting formats (e.g., COREP, FR Y 14/Q). Capital optimisation knowledge , including how RWA changes impact ROE, balance sheet usage, liquidity consumption and senior leadership metrics. Advanced data analysis capability , with experience in lineage mapping, golden source assessment and evaluating data quality across derivatives, SFTs and collateral. Process design & governance experience , capable of defining controlled, auditable and regulator aligned workflows across risk and capital functions. Stakeholder management skills , with the ability to translate technical content into business impacts for CRO, Treasury, Finance, Risk IT and Front Office audiences. Scenario & stress testing familiarity , including modelling CSA changes, MPOR scenarios, sensitivity analysis and exposure recalculation effects. AI assisted regulatory analysis experience , including NLP/LLM tools for requirement mapping, automated RTMs and interpretation comparisons. Data quality diagnostics using ML , able to identify hidden inconsistencies and capital inefficiencies using advanced pattern detection. Good to have: familiarity with Databricks Data Quality frameworks, including AI based pattern identification. Professional characteristics: analytical, structured, curious and able to operate independently in fast paced regulatory programmes. Equal Opportunity & Compliance Huron is an equal opportunity employer. We are committed to creating an inclusive and diverse workplace. All employment decisions are made without regard to race, colour, religion, gender, sexual orientation, gender identity or expression, national origin, age, disability, or any other legally protected status. Position Level Senior Associate Country United KingdomAt Huron, we're redefining what a consulting organization can be. We go beyond advice to deliver results that last. We inherit our client's challenges as if they were our own. We help them transform for the future. We advocate. We make a difference. And we intelligently, passionately, relentlessly do great work together. Whether you have years of experience or come right out of college, we invite you to explore our many opportunities. Find out how you can use your talents and develop your skills to make an impact immediately. Learn about how our culture and values provide you with the kind of environment that invites new ideas and innovation. Come see how we collaborate with each other in a culture of learning, coaching, diversity and inclusion. And hear about our unwavering commitment to make a difference in partnership with our clients, shareholders, communities and colleagues. Huron Consulting Group offers a competitive compensation and benefits package including medical, dental, and vision coverage to employees and dependents; a 401(k) plan with a generous employer match; an employee stock purchase plan; a generous Paid Time Off policy; and paid parental leave and adoption assistance. Our Wellness Program supports employee total well-being by providing free annual health screenings and coaching, bank at work, and on-site workshops, as well as ongoing programs recognizing major events in the lives of our employees throughout the year. All benefits and programs are subject to applicable eligibility requirements. Huron is fully committed to providing equal employment opportunity to job applicants and employees in recruitment, hiring, employment, compensation, benefits, promotions, transfers, training, and all other terms and conditions of employment. Huron will not discriminate on the basis of age, race, color, gender, marital status, sexual orientation, gender identity, pregnancy, national origin, religion, veteran status, physical or mental disability, genetic information, creed, citizenship or any other status protected by laws or regulations in the locations where we do business. We endeavor to maintain a drug-free workplace.
Job description: Data Engineer Location: London or Newcastle with a minimum of 2 days a week office attendance. Contract Type: Permanent Full Time. Salary: London c£70,000; Newcastle £61,250 plus civil service employer pension employer contribution of 28.9%. The deadline for applications is 5.00pm Sunday 5th July. We will be holding first stage online interviews WC 6th July followed by a final 2nd stage interviews on the 14th and 15th July. Nationality Requirement UK Nationals Nationals of Commonwealth countries who have the right to work in the UK Nationals from the EU, EEA or Switzerland with (or eligible for) status under the European Union Settlement Scheme (EUSS) We do not provide sponsorship for work visas for this position. Applicants must already meet the nationality requirements outlined above. If you have any questions regarding your eligibility, please contact the HR Service desk at . About the National Audit Office The National Audit Office (NAO) is the UK's main public sector audit body. Independent of government, we are responsible for auditing the accounts of various public sector bodies, examining the propriety of government spending, assessing risks to financial control and accountability, and reviewing the economy, efficiency and effectiveness of programmes, projects, and activities. We report directly to Parliament, through the Committee of Public Accounts of the House of Commons which uses our reports as the basis of its own investigations. We employ approx. 1,000 people, most of whom are qualified accountants, trainees, or technicians. The organisation comprises two service lines: financial audit, and value for money (VFM) audit, and has a strong core of highly talented corporate teams. The NAO welcomes applications from everyone. We value diversity in all its forms and the difference it makes to our organisation. By removing barriers and creating an inclusive culture, all our people can develop and maximise their full potential. We guarantee to interview all disabled applicants who meet the minimum criteria. The NAO supports flexible working and is happy to discuss this with you at application stage. Context and main purpose of the job This is a new vacancy created within NAO's Digital Services (DS) to expand the data team within the Audit Technology & Data pillar, with responsibility for designing, building, and maintaining the infrastructure that enables robust data ingestion process, storage, and access across the organisation. This role supports the development and continual improvement of NAO data & technology service composition and provision, enabling scalable and reliable data solutions. In this capacity, you will build and optimise data pipelines, integrate diverse data sources, and ensure the efficient movement of data across systems. You will work closely with analytics engineers, data scientists, and other stakeholders to ensure data is accessible, high quality, and fit for purpose. Your work will underpin the NAO's ability to derive insights and automate processes using corporate and client data. In this role, you will Design, develop, and maintain scalable data pipelines and ETL processes. Integrate structured and unstructured data from internal and external sources. Ensure data quality, consistency, and security across systems in alignment with the NAO's data strategy. Collaborate with analytics engineers and subject matter experts to support data modelling and transformation. Work closely with other digital roles including Cybersecurity, BI, Architecture to ensure effective delivery. Monitor and optimise performance of data infrastructure. Test, monitor, and document data architecture and engineering processes to ensure transparency and maintainability. This role reports into the Audit Data Platform Lead. This role requires regular attendance at the NAO's office either in Victoria, London, or at the office in Newcastle. Responsibilities of the role As a data engineer at the NAO, you will play a critical role in building and maintaining the technical foundation that enables data driven operations and insights. You will be responsible for architecting and managing data infrastructure, ensuring that data flows securely and efficiently across systems, and enabling downstream users to access reliable, well structured data. Your key responsibilities will include Building scalable data infrastructure - design and implement systems that support the ingestion, storage, and processing of large volumes of structured and unstructured data from internal and external sources. Developing robust data pipelines - create automated workflows that extract, transform, and load data into centralized platforms, ensuring consistency, reliability, and performance across all stages. Designing and optimising ETL processes - build and maintain efficient ETL workflows to move data from source systems into usable formats. Ensure these processes are scalable, well documented, and aligned with data quality standards. Integrating diverse data sources - connect and harmonise data from various systems (operational databases, APIs, cloud services) to create unified datasets for analysis and reporting. Collaborating across teams - work closely with analytics engineers, data scientists, and business stakeholders to understand data needs and deliver infrastructure that supports analytical and operational use cases. Ensuring data reliability and performance - monitor data systems for latency, failures, and bottlenecks. Implement performance tuning and system optimisations to maintain high availability and responsiveness. Implementing data governance and security protocols - apply best practices for data privacy, access control, and compliance. Ensure that sensitive data is protected and handled in accordance with regulatory requirements. Maintaining technical documentation - produce and update documentation for data architecture, pipeline configurations, and operational procedures to support transparency and continuity. Troubleshooting and incident response - investigate and resolve data related issues, from pipeline failures to data integrity concerns. Establish proactive monitoring and alerting systems. Supporting data accessibility - enable self service access to clean, well organised data for analysts and other users through tools, APIs, or data platforms. Keeping pace with technology - stay informed about emerging tools, frameworks, and methodologies in data engineering. Continuously evaluate and adopt innovations that improve efficiency and scalability. Key skills / competencies required Communicating between the technical and non-technical (Skill level: Awareness). You can explain why it is important to communicate technical concepts in non-technical language and understand the types of communication used with internal and external stakeholders. Data analysis and synthesis (Skill level: Working). You can undertake data profiling and source system analysis and present clear insights to colleagues to support the end use of the data. Data development process (Skill level: Working). You can design, build, and test data products based on feeds from multiple systems, using a range of storage technologies and access methods. You create repeatable and reusable products. Data innovation (Skill level: Awareness). You show awareness of opportunities for innovation with new tools and uses of data. Data integration design (Skill level: Working). You deliver data solutions in accordance with agreed organisational standards that ensure services are resilient, scalable, and future proof. Data modelling (Skill level: Working). You understand the concepts and principles of data modelling and can produce, maintain, and update relevant data models and reverse engineer models from live systems. Metadata management (Skill level: Working). You use metadata repositories to complete complex tasks such as data and systems integration impact analysis and maintain them to ensure accuracy and currency. Problem management (Skill level: Awareness). You investigate problems in systems, processes, and services and contribute to the implementation of remedies and preventative measures. Programming and build (Data Engineering) (Skill level: Working). You can design, code, test, correct, and document simple programs or scripts under direction and follow agreed standards and tools. Technical understanding (Skill level: Working). You understand core technical concepts related to the role and apply them with guidance. Testing (Skill level: Working). You review requirements and specifications, define test conditions, identify issues and risks, and report test activities and results. Essential Criteria Deep, hands on experience as a cloud based Data Engineer, ideally within Microsoft Azure environments. Expert level experience designing and delivering ETL/ELT pipelines at scale. Strong experience in data modelling, including standardisation, best practice, and semantic layer design. Advanced Python skills for data processing, optimisation, and automation. Strong SQL expertise, including T SQL and PostgreSQL. Proven experience implementing and operating medallion architecture patterns. Experience with cloud native Azure data services, including: Azure Databricks Microsoft Fabric Azure Data Factory . click apply for full job details
21/06/2026
Full time
Job description: Data Engineer Location: London or Newcastle with a minimum of 2 days a week office attendance. Contract Type: Permanent Full Time. Salary: London c£70,000; Newcastle £61,250 plus civil service employer pension employer contribution of 28.9%. The deadline for applications is 5.00pm Sunday 5th July. We will be holding first stage online interviews WC 6th July followed by a final 2nd stage interviews on the 14th and 15th July. Nationality Requirement UK Nationals Nationals of Commonwealth countries who have the right to work in the UK Nationals from the EU, EEA or Switzerland with (or eligible for) status under the European Union Settlement Scheme (EUSS) We do not provide sponsorship for work visas for this position. Applicants must already meet the nationality requirements outlined above. If you have any questions regarding your eligibility, please contact the HR Service desk at . About the National Audit Office The National Audit Office (NAO) is the UK's main public sector audit body. Independent of government, we are responsible for auditing the accounts of various public sector bodies, examining the propriety of government spending, assessing risks to financial control and accountability, and reviewing the economy, efficiency and effectiveness of programmes, projects, and activities. We report directly to Parliament, through the Committee of Public Accounts of the House of Commons which uses our reports as the basis of its own investigations. We employ approx. 1,000 people, most of whom are qualified accountants, trainees, or technicians. The organisation comprises two service lines: financial audit, and value for money (VFM) audit, and has a strong core of highly talented corporate teams. The NAO welcomes applications from everyone. We value diversity in all its forms and the difference it makes to our organisation. By removing barriers and creating an inclusive culture, all our people can develop and maximise their full potential. We guarantee to interview all disabled applicants who meet the minimum criteria. The NAO supports flexible working and is happy to discuss this with you at application stage. Context and main purpose of the job This is a new vacancy created within NAO's Digital Services (DS) to expand the data team within the Audit Technology & Data pillar, with responsibility for designing, building, and maintaining the infrastructure that enables robust data ingestion process, storage, and access across the organisation. This role supports the development and continual improvement of NAO data & technology service composition and provision, enabling scalable and reliable data solutions. In this capacity, you will build and optimise data pipelines, integrate diverse data sources, and ensure the efficient movement of data across systems. You will work closely with analytics engineers, data scientists, and other stakeholders to ensure data is accessible, high quality, and fit for purpose. Your work will underpin the NAO's ability to derive insights and automate processes using corporate and client data. In this role, you will Design, develop, and maintain scalable data pipelines and ETL processes. Integrate structured and unstructured data from internal and external sources. Ensure data quality, consistency, and security across systems in alignment with the NAO's data strategy. Collaborate with analytics engineers and subject matter experts to support data modelling and transformation. Work closely with other digital roles including Cybersecurity, BI, Architecture to ensure effective delivery. Monitor and optimise performance of data infrastructure. Test, monitor, and document data architecture and engineering processes to ensure transparency and maintainability. This role reports into the Audit Data Platform Lead. This role requires regular attendance at the NAO's office either in Victoria, London, or at the office in Newcastle. Responsibilities of the role As a data engineer at the NAO, you will play a critical role in building and maintaining the technical foundation that enables data driven operations and insights. You will be responsible for architecting and managing data infrastructure, ensuring that data flows securely and efficiently across systems, and enabling downstream users to access reliable, well structured data. Your key responsibilities will include Building scalable data infrastructure - design and implement systems that support the ingestion, storage, and processing of large volumes of structured and unstructured data from internal and external sources. Developing robust data pipelines - create automated workflows that extract, transform, and load data into centralized platforms, ensuring consistency, reliability, and performance across all stages. Designing and optimising ETL processes - build and maintain efficient ETL workflows to move data from source systems into usable formats. Ensure these processes are scalable, well documented, and aligned with data quality standards. Integrating diverse data sources - connect and harmonise data from various systems (operational databases, APIs, cloud services) to create unified datasets for analysis and reporting. Collaborating across teams - work closely with analytics engineers, data scientists, and business stakeholders to understand data needs and deliver infrastructure that supports analytical and operational use cases. Ensuring data reliability and performance - monitor data systems for latency, failures, and bottlenecks. Implement performance tuning and system optimisations to maintain high availability and responsiveness. Implementing data governance and security protocols - apply best practices for data privacy, access control, and compliance. Ensure that sensitive data is protected and handled in accordance with regulatory requirements. Maintaining technical documentation - produce and update documentation for data architecture, pipeline configurations, and operational procedures to support transparency and continuity. Troubleshooting and incident response - investigate and resolve data related issues, from pipeline failures to data integrity concerns. Establish proactive monitoring and alerting systems. Supporting data accessibility - enable self service access to clean, well organised data for analysts and other users through tools, APIs, or data platforms. Keeping pace with technology - stay informed about emerging tools, frameworks, and methodologies in data engineering. Continuously evaluate and adopt innovations that improve efficiency and scalability. Key skills / competencies required Communicating between the technical and non-technical (Skill level: Awareness). You can explain why it is important to communicate technical concepts in non-technical language and understand the types of communication used with internal and external stakeholders. Data analysis and synthesis (Skill level: Working). You can undertake data profiling and source system analysis and present clear insights to colleagues to support the end use of the data. Data development process (Skill level: Working). You can design, build, and test data products based on feeds from multiple systems, using a range of storage technologies and access methods. You create repeatable and reusable products. Data innovation (Skill level: Awareness). You show awareness of opportunities for innovation with new tools and uses of data. Data integration design (Skill level: Working). You deliver data solutions in accordance with agreed organisational standards that ensure services are resilient, scalable, and future proof. Data modelling (Skill level: Working). You understand the concepts and principles of data modelling and can produce, maintain, and update relevant data models and reverse engineer models from live systems. Metadata management (Skill level: Working). You use metadata repositories to complete complex tasks such as data and systems integration impact analysis and maintain them to ensure accuracy and currency. Problem management (Skill level: Awareness). You investigate problems in systems, processes, and services and contribute to the implementation of remedies and preventative measures. Programming and build (Data Engineering) (Skill level: Working). You can design, code, test, correct, and document simple programs or scripts under direction and follow agreed standards and tools. Technical understanding (Skill level: Working). You understand core technical concepts related to the role and apply them with guidance. Testing (Skill level: Working). You review requirements and specifications, define test conditions, identify issues and risks, and report test activities and results. Essential Criteria Deep, hands on experience as a cloud based Data Engineer, ideally within Microsoft Azure environments. Expert level experience designing and delivering ETL/ELT pipelines at scale. Strong experience in data modelling, including standardisation, best practice, and semantic layer design. Advanced Python skills for data processing, optimisation, and automation. Strong SQL expertise, including T SQL and PostgreSQL. Proven experience implementing and operating medallion architecture patterns. Experience with cloud native Azure data services, including: Azure Databricks Microsoft Fabric Azure Data Factory . click apply for full job details
