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.
20/07/2026
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.
Fancy helping us shape the future of motor insurance? Prima could be the place for you. Since 2015, we've been using our love of data and tech to rethink motor insurance and bring drivers a great experience at a great price. Our story began in Italy, where we've quickly become the number one online motor insurance provider. In fact, we're trusted by over 5 million drivers. And now we're expanding to help millions more drivers in the UK and Spain. To help fuel that growth, we need a Senior Data Engineer to join our Engineering team. This team is the beating heart of Prima. You'll be joining over 350 engineers across software development, infrastructure, operations, and security. Fueled by curiosity, experimentation, and collaboration, you'll help deliver scalable, impactful solutions that shape the future of insurance. Excited to make an impact? Here are the details You'll be joining our Pricing and Underwriting domain to bridge the gap between machine learning/data science and engineering. You will help build, publish, and maintain our complex data products and pipelines - key elements with a significant impact on the company's growth. What you'll do Shape the architecture of data products designed for: data analytics forecasting feature engineering customer behavior analysis integration of new data sources Data Transformation & Governance Lead best practices in: data modelling performance optimization data governance consistent available reliable Build reusable technology enabling teams to: ingest data store data transform data serve their own data products Collaboration & Product Thinking Work closely with: data scientists machine learning engineers Refine data requirements and evolve infrastructure capabilities Stay updated with emerging technologies Experiment with open source tools Participate in community-building initiatives such as meetups Continuously learn and improve engineering practices What we're looking for batch processing distributed data processing Experience with technologies such as: Kafka Flink Spark Databricks experience is a plus Experience implementing: Data Lakes Big Data Analytics platforms Cloud-based solutions experience AWS preferred Software Engineering Expertise with: RDBMS Data Warehousing Data Modelling Experience with: Redshift PostgreSQL NoSQL databases DevOps & Infrastructure Proficiency in: DevOps practices CI/CD pipeline management Infrastructure as Code (IaC) Nice-to-Have Hands-on experience with: Data Quality Data Governance techniques Knowledge of: MLOps Feature Engineering Exposure to data analysis and ML tools such as: scikit-learn pandas NumPy XGBoost LightGBM Familiarity with orchestration tools: Apache Oozie Apache Airflow Why you'll love it here We want to make Prima a happy and empowering place to work. So if you decide to join us, you can expect plenty of perks. Enjoy full flexibility - work from home, the office, or a mix of both. Plus, work from anywhere for up to 30 days a year. Grow with us We may move fast at Prima, but we move together. Get access to learning resources, mentorship, and a growth plan tailored to you. Thrive and perform Your best work begins when you feel your best. Enjoy private healthcare, gym discounts, wellbeing programs, and mental health support.
19/07/2026
Full time
Fancy helping us shape the future of motor insurance? Prima could be the place for you. Since 2015, we've been using our love of data and tech to rethink motor insurance and bring drivers a great experience at a great price. Our story began in Italy, where we've quickly become the number one online motor insurance provider. In fact, we're trusted by over 5 million drivers. And now we're expanding to help millions more drivers in the UK and Spain. To help fuel that growth, we need a Senior Data Engineer to join our Engineering team. This team is the beating heart of Prima. You'll be joining over 350 engineers across software development, infrastructure, operations, and security. Fueled by curiosity, experimentation, and collaboration, you'll help deliver scalable, impactful solutions that shape the future of insurance. Excited to make an impact? Here are the details You'll be joining our Pricing and Underwriting domain to bridge the gap between machine learning/data science and engineering. You will help build, publish, and maintain our complex data products and pipelines - key elements with a significant impact on the company's growth. What you'll do Shape the architecture of data products designed for: data analytics forecasting feature engineering customer behavior analysis integration of new data sources Data Transformation & Governance Lead best practices in: data modelling performance optimization data governance consistent available reliable Build reusable technology enabling teams to: ingest data store data transform data serve their own data products Collaboration & Product Thinking Work closely with: data scientists machine learning engineers Refine data requirements and evolve infrastructure capabilities Stay updated with emerging technologies Experiment with open source tools Participate in community-building initiatives such as meetups Continuously learn and improve engineering practices What we're looking for batch processing distributed data processing Experience with technologies such as: Kafka Flink Spark Databricks experience is a plus Experience implementing: Data Lakes Big Data Analytics platforms Cloud-based solutions experience AWS preferred Software Engineering Expertise with: RDBMS Data Warehousing Data Modelling Experience with: Redshift PostgreSQL NoSQL databases DevOps & Infrastructure Proficiency in: DevOps practices CI/CD pipeline management Infrastructure as Code (IaC) Nice-to-Have Hands-on experience with: Data Quality Data Governance techniques Knowledge of: MLOps Feature Engineering Exposure to data analysis and ML tools such as: scikit-learn pandas NumPy XGBoost LightGBM Familiarity with orchestration tools: Apache Oozie Apache Airflow Why you'll love it here We want to make Prima a happy and empowering place to work. So if you decide to join us, you can expect plenty of perks. Enjoy full flexibility - work from home, the office, or a mix of both. Plus, work from anywhere for up to 30 days a year. Grow with us We may move fast at Prima, but we move together. Get access to learning resources, mentorship, and a growth plan tailored to you. Thrive and perform Your best work begins when you feel your best. Enjoy private healthcare, gym discounts, wellbeing programs, and mental health support.
Job Role We are looking for a Data Engineer to design, build and operate scalable data pipelines and data platform capabilities within a modern lakehouse architecture. You will work in a collaborative agile engineering team delivering production grade data solutions using Databricks, Spark, Python and SQL in a cloud environment. The role focuses on developing robust data pipelines, ensuring high data quality and enabling analytics and data product delivery for enterprise clients. Key Responsibilities Design and implement ELT/ETL pipelines using PySpark and Databricks Build scalable batch and streaming data pipelines using Spark and Kafka, develop optimised SQL and Python pipelines for data transformation and integration, and integrate external data sources using REST APIs and data ingestion frameworks Optimise Spark jobs and cluster performance for reliability and cost efficiency, implement data quality checks, validation and monitoring Apply CI/CD practices and version control for pipeline deployment Work closely with solution architects, DevOps engineers and business analysts to deliver data products, produce technical documentation, architecture diagrams and operational runbooks Key Requirements 3+ years experience building production data pipelines Hands on experience with Databricks, Spark and PySpark; experience with Delta Lake, Unity Catalog and Databricks Working experience with data pipeline design, testing and deployment; familiarity with test driven development, CI/CD practices and Git based development Strong collaboration and communication skills Working knowledge of Hadoop REST APIs and Kafka experience Nice to Have Cloud experience with AWS, Azure or GCP; certifications in Databricks, AWS or data engineering Infrastructure as Code (Terraform); orchestration with Airflow or AWS Glue; streaming technologies including Structured Streaming; observability tooling for data pipelines Experience working with regulated industries such as banking or financial services Databricks experience is preferred; training will be offered to strong candidates.
19/07/2026
Full time
Job Role We are looking for a Data Engineer to design, build and operate scalable data pipelines and data platform capabilities within a modern lakehouse architecture. You will work in a collaborative agile engineering team delivering production grade data solutions using Databricks, Spark, Python and SQL in a cloud environment. The role focuses on developing robust data pipelines, ensuring high data quality and enabling analytics and data product delivery for enterprise clients. Key Responsibilities Design and implement ELT/ETL pipelines using PySpark and Databricks Build scalable batch and streaming data pipelines using Spark and Kafka, develop optimised SQL and Python pipelines for data transformation and integration, and integrate external data sources using REST APIs and data ingestion frameworks Optimise Spark jobs and cluster performance for reliability and cost efficiency, implement data quality checks, validation and monitoring Apply CI/CD practices and version control for pipeline deployment Work closely with solution architects, DevOps engineers and business analysts to deliver data products, produce technical documentation, architecture diagrams and operational runbooks Key Requirements 3+ years experience building production data pipelines Hands on experience with Databricks, Spark and PySpark; experience with Delta Lake, Unity Catalog and Databricks Working experience with data pipeline design, testing and deployment; familiarity with test driven development, CI/CD practices and Git based development Strong collaboration and communication skills Working knowledge of Hadoop REST APIs and Kafka experience Nice to Have Cloud experience with AWS, Azure or GCP; certifications in Databricks, AWS or data engineering Infrastructure as Code (Terraform); orchestration with Airflow or AWS Glue; streaming technologies including Structured Streaming; observability tooling for data pipelines Experience working with regulated industries such as banking or financial services Databricks experience is preferred; training will be offered to strong candidates.
JPMorganChase is seeking a Software Engineer III to join the AI/ML and Data Platform team in the UK. You will design and deliver trusted, scalable software solutions in a secure environment, working within an agile team to meet business objectives. The role emphasizes production-grade code, automation, and collaboration with data and application teams. Strong Python/Java, CI/CD, and AWS Databricks experience are required, with a focus on secure, resilient systems.
19/07/2026
Full time
JPMorganChase is seeking a Software Engineer III to join the AI/ML and Data Platform team in the UK. You will design and deliver trusted, scalable software solutions in a secure environment, working within an agile team to meet business objectives. The role emphasizes production-grade code, automation, and collaboration with data and application teams. Strong Python/Java, CI/CD, and AWS Databricks experience are required, with a focus on secure, resilient systems.
Job Description My client, a global manufacturing and engineering organisation, is seeking a Data Scientist - Analytics & Machine Learning to join their Business Solutions team in Northern Ireland. This role can be based across multiple sites and will support a large-scale manufacturing operation through the delivery of data-driven insights, advanced analytics, and AI-enabled solutions. Competitive salary and benefits package Hybrid and flexible working options Pension scheme and healthcare benefits Employee share purchase scheme Ongoing training and professional development International project exposure Clear career progression opportunities This role will support key business functions across operations, engineering, supply chain, and commercial teams by leveraging data, analytics, machine learning, and AI to improve decision-making and business performance. Working closely with stakeholders across the organisation, you will identify opportunities where advanced analytics can deliver measurable value and help transform complex business challenges into actionable insights. This is a hands on position focused on delivering real world business outcomes through data science, predictive analytics, reporting, and machine learning initiatives. Business Understanding & Insight Delivery Develop a strong understanding of business processes across operations, engineering, supply chain, and commercial functions. Partner with operational leaders and digital transformation teams to identify analytics and AI opportunities. Translate business challenges into practical data and AI use cases with measurable outcomes. Provide data driven recommendations that support operational efficiency and performance improvement. Data Analytics, AI & Machine Learning Deliver descriptive, diagnostic, and predictive analytics to improve business performance. Support machine learning and AI initiatives through: Data exploration and preparation Model development and evaluation Dashboarding and insight generation Prepare, cleanse, and rationalise data for analytics and AI projects. Identify trends, risks, and opportunities within complex datasets. Data Platforms & Reporting Work with enterprise data platforms and cloud based data environments. Query, analyse, and model data using modern analytics technologies. Develop and maintain dashboards and visualisations using Power BI or similar tools. Support the evolution of reporting and analytics capabilities across the business. Systems Integration & Collaboration Collaborate with IT and business teams on data integration initiatives. Support integrations across reporting platforms, operational systems, ERP solutions, and analytics environments. Ensure compliance with data governance, security, and best practice standards. Contribute to continuous improvement initiatives across data and analytics functions. The Person Essential Criteria Degree qualification in Data Science, Computer Science, Engineering, Mathematics, Analytics, or a related discipline. Commercial experience working with data analytics, machine learning, or AI solutions. Strong experience with Python, SQL, or similar analytics technologies. Experience working with enterprise data platforms and cloud based environments. Experience designing and delivering reporting or analytics solutions using Power BI or similar BI tools. Understanding of data integration, enterprise systems, and operational business processes. Knowledge of data governance, security, and compliance frameworks. Strong communication skills with the ability to engage both technical and non-technical stakeholders. Ability to work effectively across business and IT teams. Desirable Criteria Experience within manufacturing, engineering, industrial, or operational environments. Exposure to cloud platforms such as AWS, Azure, Snowflake, Databricks, or similar technologies. Experience with ERP, MES, or other enterprise operational systems. Experience supporting AI enabled analytics or machine learning projects. Key Skills Strong commercial awareness. Excellent analytical and problem solving skills. Strong organisational and planning abilities. Ability to manage multiple priorities effectively. High attention to detail and documentation standards. Self motivated and proactive approach. Adaptable and resilient in a fast paced environment. Excellent communication and stakeholder management skills. Ability to deliver training and support to business users. Additional Information Travel between company locations may be required. Occasional international travel may be required (up to 25%). Candidates who may not meet every requirement but possess relevant experience are encouraged to apply. For further information on this opportunity, or any other Data Science, AI, Analytics, Machine Learning, or Data Engineering roles in Northern Ireland, apply via the link or contact the recruitment team for a confidential discussion.
19/07/2026
Full time
Job Description My client, a global manufacturing and engineering organisation, is seeking a Data Scientist - Analytics & Machine Learning to join their Business Solutions team in Northern Ireland. This role can be based across multiple sites and will support a large-scale manufacturing operation through the delivery of data-driven insights, advanced analytics, and AI-enabled solutions. Competitive salary and benefits package Hybrid and flexible working options Pension scheme and healthcare benefits Employee share purchase scheme Ongoing training and professional development International project exposure Clear career progression opportunities This role will support key business functions across operations, engineering, supply chain, and commercial teams by leveraging data, analytics, machine learning, and AI to improve decision-making and business performance. Working closely with stakeholders across the organisation, you will identify opportunities where advanced analytics can deliver measurable value and help transform complex business challenges into actionable insights. This is a hands on position focused on delivering real world business outcomes through data science, predictive analytics, reporting, and machine learning initiatives. Business Understanding & Insight Delivery Develop a strong understanding of business processes across operations, engineering, supply chain, and commercial functions. Partner with operational leaders and digital transformation teams to identify analytics and AI opportunities. Translate business challenges into practical data and AI use cases with measurable outcomes. Provide data driven recommendations that support operational efficiency and performance improvement. Data Analytics, AI & Machine Learning Deliver descriptive, diagnostic, and predictive analytics to improve business performance. Support machine learning and AI initiatives through: Data exploration and preparation Model development and evaluation Dashboarding and insight generation Prepare, cleanse, and rationalise data for analytics and AI projects. Identify trends, risks, and opportunities within complex datasets. Data Platforms & Reporting Work with enterprise data platforms and cloud based data environments. Query, analyse, and model data using modern analytics technologies. Develop and maintain dashboards and visualisations using Power BI or similar tools. Support the evolution of reporting and analytics capabilities across the business. Systems Integration & Collaboration Collaborate with IT and business teams on data integration initiatives. Support integrations across reporting platforms, operational systems, ERP solutions, and analytics environments. Ensure compliance with data governance, security, and best practice standards. Contribute to continuous improvement initiatives across data and analytics functions. The Person Essential Criteria Degree qualification in Data Science, Computer Science, Engineering, Mathematics, Analytics, or a related discipline. Commercial experience working with data analytics, machine learning, or AI solutions. Strong experience with Python, SQL, or similar analytics technologies. Experience working with enterprise data platforms and cloud based environments. Experience designing and delivering reporting or analytics solutions using Power BI or similar BI tools. Understanding of data integration, enterprise systems, and operational business processes. Knowledge of data governance, security, and compliance frameworks. Strong communication skills with the ability to engage both technical and non-technical stakeholders. Ability to work effectively across business and IT teams. Desirable Criteria Experience within manufacturing, engineering, industrial, or operational environments. Exposure to cloud platforms such as AWS, Azure, Snowflake, Databricks, or similar technologies. Experience with ERP, MES, or other enterprise operational systems. Experience supporting AI enabled analytics or machine learning projects. Key Skills Strong commercial awareness. Excellent analytical and problem solving skills. Strong organisational and planning abilities. Ability to manage multiple priorities effectively. High attention to detail and documentation standards. Self motivated and proactive approach. Adaptable and resilient in a fast paced environment. Excellent communication and stakeholder management skills. Ability to deliver training and support to business users. Additional Information Travel between company locations may be required. Occasional international travel may be required (up to 25%). Candidates who may not meet every requirement but possess relevant experience are encouraged to apply. For further information on this opportunity, or any other Data Science, AI, Analytics, Machine Learning, or Data Engineering roles in Northern Ireland, apply via the link or contact the recruitment team for a confidential discussion.
We have an exciting and rewarding opportunity for you to take your software engineering career to the next level. As a Software Engineer III at JPMorganChase within the AI/ML and Data Platform, you serve as a seasoned member of an agile team to design and deliver trusted market leading technology products in a secure, stable, and scalable way. You are responsible for carrying out critical technology solutions across multiple technical areas within various business functions in support of the firm's business objectives. Job responsibilities Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems. Creates secure and high quality production code and maintains algorithms that run synchronously with appropriate systems. Performs platform design, set up and configuration, providing engineering support to data engineering teams, Data Science/ML, and Application/integration teams. Collaborates with engineering and data teams to optimize infrastructure and deployment processes, focusing on automation and operational excellence. Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems. Leverages enterprise authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity across complex deliverables (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards; contributes learnings and reusable patterns to improve broader team effectiveness. Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise authorized AI assisted development and automation capabilities, to improve the value realized by automation. Leads evaluation sessions with external vendors, startups, and internal teams to drive outcomes oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture. Contributes to software engineering communities of practice and events that explore new and emerging technologies Adds to team culture of diversity, opportunity, inclusion, and respect Required qualifications, capabilities, and skills Formal training or certification on software engineering concepts and applied experience. Extensive experience with AWS Databricks platform administration and engineering support is a MUST. Strong understanding of SRE principles, including SLIs, SLOs, error budgets, and incident management. Experience with monitoring tools, automation frameworks, and CI/CD pipelines. Hands on experience using enterprise authorized AI assisted software development tools within the work environment (e.g., for coding, test creation, troubleshooting, or documentation) with demonstrated ability to critically evaluate, validate, and refine AI generated outputs for correctness, performance, and security. Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; ability to guide peers on safe and effective usage within team practices. Proficient in Python and/or Java application program development with use of automated unit testing. Solid understanding of agile methodologies such as CI/CD, Application Resiliency, and Security Knowledge of Big Data distributed compute frameworks like Spark, Glue, MapReduce etc. Excellent troubleshooting, analytical, and communication skills. Preferred qualifications, capabilities, and skills Experience in Data pipelines using Spark Exposure to AWS & Databricks Platform administration. Knowledge of containerization (Docker, Kubernetes) and orchestration. Familiarity with distributed systems and large scale data processing.
19/07/2026
Full time
We have an exciting and rewarding opportunity for you to take your software engineering career to the next level. As a Software Engineer III at JPMorganChase within the AI/ML and Data Platform, you serve as a seasoned member of an agile team to design and deliver trusted market leading technology products in a secure, stable, and scalable way. You are responsible for carrying out critical technology solutions across multiple technical areas within various business functions in support of the firm's business objectives. Job responsibilities Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems. Creates secure and high quality production code and maintains algorithms that run synchronously with appropriate systems. Performs platform design, set up and configuration, providing engineering support to data engineering teams, Data Science/ML, and Application/integration teams. Collaborates with engineering and data teams to optimize infrastructure and deployment processes, focusing on automation and operational excellence. Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems. Leverages enterprise authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity across complex deliverables (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards; contributes learnings and reusable patterns to improve broader team effectiveness. Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise authorized AI assisted development and automation capabilities, to improve the value realized by automation. Leads evaluation sessions with external vendors, startups, and internal teams to drive outcomes oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture. Contributes to software engineering communities of practice and events that explore new and emerging technologies Adds to team culture of diversity, opportunity, inclusion, and respect Required qualifications, capabilities, and skills Formal training or certification on software engineering concepts and applied experience. Extensive experience with AWS Databricks platform administration and engineering support is a MUST. Strong understanding of SRE principles, including SLIs, SLOs, error budgets, and incident management. Experience with monitoring tools, automation frameworks, and CI/CD pipelines. Hands on experience using enterprise authorized AI assisted software development tools within the work environment (e.g., for coding, test creation, troubleshooting, or documentation) with demonstrated ability to critically evaluate, validate, and refine AI generated outputs for correctness, performance, and security. Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; ability to guide peers on safe and effective usage within team practices. Proficient in Python and/or Java application program development with use of automated unit testing. Solid understanding of agile methodologies such as CI/CD, Application Resiliency, and Security Knowledge of Big Data distributed compute frameworks like Spark, Glue, MapReduce etc. Excellent troubleshooting, analytical, and communication skills. Preferred qualifications, capabilities, and skills Experience in Data pipelines using Spark Exposure to AWS & Databricks Platform administration. Knowledge of containerization (Docker, Kubernetes) and orchestration. Familiarity with distributed systems and large scale data processing.
Senior Data Engineer (Senior Associate) As a Senior Data Engineer (Senior Associate) at Kainos, you will be responsible for designing and developing data processing and data persistence software components for solutions that handle data at scale. Working in agile teams, Senior Data Engineers provide strong development leadership and take responsibility for significant technical components of data systems. You will work within a multi-skilled agile team to design and develop large-scale data processing software to meet user needs in demanding production environments. Your Responsibilities Will Include Working to develop data processing software primarily for deployment in Big Data technologies. The role encompasses the full software lifecycle, including design, code, test, and defect resolution. Working with Architects and Lead Engineers to ensure the software supports non functional needs. Collaborating with colleagues to resolve implementation challenges and ensure code quality and maintainability remains high, leading by example in code quality. Working with operations teams to ensure operational readiness. Advising customers and managers on the estimated effort and technical implications of user stories and user journeys. Coaching and mentoring team members. Minimum (Essential) Requirements Strong software development experience in one of Java, Scala, or Python. Software development experience with data processing platforms from vendors such as AWS, Azure, GCP, and Databricks. Experience of developing substantial components for large scale data processing solutions and deploying them into a production environment. Proficient in SQL and SQL extensions for analytical queries. Solid understanding of ETL/ELT data processing pipelines and design patterns. Aware of key features and pitfalls of distributed data processing frameworks, data stores, and data serialization formats. Ability to write quality, testable code and experience with automated testing. Experience with Continuous Integration and Continuous Deployment techniques. Keen interest in AI technologies. Desirable Requirements Experience of performance tuning. Experience of data visualization and complex data transformations. Experience with streaming and event processing architectures, including technologies such as Kafka and change data capture (CDC) products. Expertise in continuous improvement and sharing input on data best practices. Practical experience with AI technologies, tools, processes, and delivery. Embracing Our Differences At Kainos, we believe in the power of diversity, equity and inclusion. We are committed to building a team that is as diverse as the world we live in, where everyone is valued, respected, and given an equal chance to thrive. We actively seek out talented people from all backgrounds, regardless of age, race, ethnicity, gender, sexual orientation, religion, disability, or any other characteristic that makes them who they are. We also believe every candidate deserves a level playing field. Our friendly talent acquisition team is here to support you every step of the way, so if you require any accommodations or adjustments, we encourage you to reach out. We understand that everyone's journey is different, and by having a private conversation we can ensure that our recruitment process is tailored to your needs.
19/07/2026
Full time
Senior Data Engineer (Senior Associate) As a Senior Data Engineer (Senior Associate) at Kainos, you will be responsible for designing and developing data processing and data persistence software components for solutions that handle data at scale. Working in agile teams, Senior Data Engineers provide strong development leadership and take responsibility for significant technical components of data systems. You will work within a multi-skilled agile team to design and develop large-scale data processing software to meet user needs in demanding production environments. Your Responsibilities Will Include Working to develop data processing software primarily for deployment in Big Data technologies. The role encompasses the full software lifecycle, including design, code, test, and defect resolution. Working with Architects and Lead Engineers to ensure the software supports non functional needs. Collaborating with colleagues to resolve implementation challenges and ensure code quality and maintainability remains high, leading by example in code quality. Working with operations teams to ensure operational readiness. Advising customers and managers on the estimated effort and technical implications of user stories and user journeys. Coaching and mentoring team members. Minimum (Essential) Requirements Strong software development experience in one of Java, Scala, or Python. Software development experience with data processing platforms from vendors such as AWS, Azure, GCP, and Databricks. Experience of developing substantial components for large scale data processing solutions and deploying them into a production environment. Proficient in SQL and SQL extensions for analytical queries. Solid understanding of ETL/ELT data processing pipelines and design patterns. Aware of key features and pitfalls of distributed data processing frameworks, data stores, and data serialization formats. Ability to write quality, testable code and experience with automated testing. Experience with Continuous Integration and Continuous Deployment techniques. Keen interest in AI technologies. Desirable Requirements Experience of performance tuning. Experience of data visualization and complex data transformations. Experience with streaming and event processing architectures, including technologies such as Kafka and change data capture (CDC) products. Expertise in continuous improvement and sharing input on data best practices. Practical experience with AI technologies, tools, processes, and delivery. Embracing Our Differences At Kainos, we believe in the power of diversity, equity and inclusion. We are committed to building a team that is as diverse as the world we live in, where everyone is valued, respected, and given an equal chance to thrive. We actively seek out talented people from all backgrounds, regardless of age, race, ethnicity, gender, sexual orientation, religion, disability, or any other characteristic that makes them who they are. We also believe every candidate deserves a level playing field. Our friendly talent acquisition team is here to support you every step of the way, so if you require any accommodations or adjustments, we encourage you to reach out. We understand that everyone's journey is different, and by having a private conversation we can ensure that our recruitment process is tailored to your needs.
The DevOps Engineer is responsible for building, deploying, and maintaining infrastructure that supports Jumping Rivers' clients, with a particular focus on Posit product deployments across cloud and on premises environments. The role combines infrastructure engineering, automation, and CI/CD pipeline management with hands on client support, ensuring systems are deployed to a high standard and remain secure, scalable, and reliable once live. Key Accountabilities Infrastructure Deployment (40%) Deploy and configure Posit Connect, Posit Workbench, and Posit Package Manager for clients across AWS, Azure, GCP, and on premise environments Provision infrastructure using Infrastructure-as-Code tools (e.g. Terraform, Ansible) Configure authentication, SSO, and access control integrations (e.g. LDAP, SAML, OAuth) Set up networking, security, and compliance configurations (VPCs, firewalls, SSL/TLS) Work with containerisation and orchestration tools (Docker, Kubernetes) where relevant to deployment architecture CI/CD & Automation (20%) Design, build, and maintain CI/CD pipelines for client deployments Develop scripts and tooling to automate repeatable deployment and configuration tasks Contribute to internal tooling that improves deployment speed, consistency, and reliability Support & Maintenance (30%) Monitor, troubleshoot, and maintain Posit systems post deployment Apply patches, upgrades, and version updates to Posit products and underlying infrastructure Diagnose and resolve infrastructure, networking, and application level issues Support performance tuning and capacity planning across client environments Client Liaison & Collaboration (10%) Liaise directly with clients to scope infrastructure requirements and troubleshoot issues Communicate technical work clearly to non technical stakeholders Collaborate with data scientists to ensure infrastructure meets project needs Write and maintain clear technical documentation for deployments and support processes Academic Qualifications Degree in Computer Science, Software Engineering, IT, or a related technical field, or equivalent professional experience Relevant cloud or infrastructure certifications (e.g. AWS, Azure, GCP) are desirable but not essential Skills and Experience Technical Skills Essential Experience in a DevOps, infrastructure, or systems engineering role Hands on experience with at least one major cloud provider (AWS, Azure, or GCP) Experience with Infrastructure-as-Code (Terraform, Ansible, or similar) Comfortable working in Linux environments Understanding of networking fundamentals (DNS, load balancing, VPNs, firewalls) Strong, methodical troubleshooting skills Desirable Direct experience deploying or administering data science software Familiarity with R and/or Python ecosystems Experience with containerisation (Docker/Kubernetes) Scripting experience (Bash, Python) for automation Experience with monitoring/observability tooling (Grafana or similar) Experience with Databricks Soft Skills Experience working in a consultancy or client facing environment Excellent communication skills, with the ability to explain technical issues to non technical clients Ability to manage multiple client deployments and support requests concurrently Can demonstrate initiative and ownership of tasks Experienced in owning the delivery of individual work from start to finish
19/07/2026
Full time
The DevOps Engineer is responsible for building, deploying, and maintaining infrastructure that supports Jumping Rivers' clients, with a particular focus on Posit product deployments across cloud and on premises environments. The role combines infrastructure engineering, automation, and CI/CD pipeline management with hands on client support, ensuring systems are deployed to a high standard and remain secure, scalable, and reliable once live. Key Accountabilities Infrastructure Deployment (40%) Deploy and configure Posit Connect, Posit Workbench, and Posit Package Manager for clients across AWS, Azure, GCP, and on premise environments Provision infrastructure using Infrastructure-as-Code tools (e.g. Terraform, Ansible) Configure authentication, SSO, and access control integrations (e.g. LDAP, SAML, OAuth) Set up networking, security, and compliance configurations (VPCs, firewalls, SSL/TLS) Work with containerisation and orchestration tools (Docker, Kubernetes) where relevant to deployment architecture CI/CD & Automation (20%) Design, build, and maintain CI/CD pipelines for client deployments Develop scripts and tooling to automate repeatable deployment and configuration tasks Contribute to internal tooling that improves deployment speed, consistency, and reliability Support & Maintenance (30%) Monitor, troubleshoot, and maintain Posit systems post deployment Apply patches, upgrades, and version updates to Posit products and underlying infrastructure Diagnose and resolve infrastructure, networking, and application level issues Support performance tuning and capacity planning across client environments Client Liaison & Collaboration (10%) Liaise directly with clients to scope infrastructure requirements and troubleshoot issues Communicate technical work clearly to non technical stakeholders Collaborate with data scientists to ensure infrastructure meets project needs Write and maintain clear technical documentation for deployments and support processes Academic Qualifications Degree in Computer Science, Software Engineering, IT, or a related technical field, or equivalent professional experience Relevant cloud or infrastructure certifications (e.g. AWS, Azure, GCP) are desirable but not essential Skills and Experience Technical Skills Essential Experience in a DevOps, infrastructure, or systems engineering role Hands on experience with at least one major cloud provider (AWS, Azure, or GCP) Experience with Infrastructure-as-Code (Terraform, Ansible, or similar) Comfortable working in Linux environments Understanding of networking fundamentals (DNS, load balancing, VPNs, firewalls) Strong, methodical troubleshooting skills Desirable Direct experience deploying or administering data science software Familiarity with R and/or Python ecosystems Experience with containerisation (Docker/Kubernetes) Scripting experience (Bash, Python) for automation Experience with monitoring/observability tooling (Grafana or similar) Experience with Databricks Soft Skills Experience working in a consultancy or client facing environment Excellent communication skills, with the ability to explain technical issues to non technical clients Ability to manage multiple client deployments and support requests concurrently Can demonstrate initiative and ownership of tasks Experienced in owning the delivery of individual work from start to finish
Lead Data Analyst - Commercial Analytics In just 10 years, Octopus Energy has evolved from a disruptive challenger into the UK's largest energy retailer and a well-loved brand, serving more than 8 million customers. Key Responsibilities Own end-to-end pricing operations for domestic tariffs, including launches, quarterly price changes, margin reporting and intelligence, and ensuring regulatory / price cap compliance for millions of customers. Drive pricing strategy and optimisation through competitor intelligence, market analysis, and data-driven recommendations to the Senior Leadership Team. Own and evolve commercial reporting pipelines across customer switching, sales activity from all channels, marketing campaigns, retention and competitor insight. Deliver growth and customer insight, including key metric reporting, funnel analysis, customer forecasting, and retention initiatives. Set priorities, coordinate and review the work of a small, high-performance team of data analysts. Partner with Commercial, Sales, Marketing, Energy Markets, Flexibility, Gross Margin and Strategic Finance teams to provide customer forecasting inputs, KPI reporting, margin analysis and strategic support. Contribute to and collaborate with our global working groups to ensure aligned reporting and shared analytics projects. Champion data best practices and continuous improvement in analytics engineering, tools and automated processes. Requirements Hands-on expertise with modern data platforms and analytical tools (especially SQL and python - see our full stack below). Strong commercial acumen, preferably in pricing, margin optimisation, and/or growth analytics. Proven experience mentoring and developing data professionals. Strong communication skills to influence non-technical stakeholders and senior leadership. A track record of delivering actionable insights that drive measurable business impact. Python, pandas and SQL in Jupyter notebooks for analysis dbt and Databricks data platform with Delta Lake Lightdash as our BI tool and semantic layer Streamlit for interactive data applications Airflow for orchestration CI/CD with GitHub and CircleCI Infrastructure on AWS, deployed with Terraform / Spacelift
19/07/2026
Full time
Lead Data Analyst - Commercial Analytics In just 10 years, Octopus Energy has evolved from a disruptive challenger into the UK's largest energy retailer and a well-loved brand, serving more than 8 million customers. Key Responsibilities Own end-to-end pricing operations for domestic tariffs, including launches, quarterly price changes, margin reporting and intelligence, and ensuring regulatory / price cap compliance for millions of customers. Drive pricing strategy and optimisation through competitor intelligence, market analysis, and data-driven recommendations to the Senior Leadership Team. Own and evolve commercial reporting pipelines across customer switching, sales activity from all channels, marketing campaigns, retention and competitor insight. Deliver growth and customer insight, including key metric reporting, funnel analysis, customer forecasting, and retention initiatives. Set priorities, coordinate and review the work of a small, high-performance team of data analysts. Partner with Commercial, Sales, Marketing, Energy Markets, Flexibility, Gross Margin and Strategic Finance teams to provide customer forecasting inputs, KPI reporting, margin analysis and strategic support. Contribute to and collaborate with our global working groups to ensure aligned reporting and shared analytics projects. Champion data best practices and continuous improvement in analytics engineering, tools and automated processes. Requirements Hands-on expertise with modern data platforms and analytical tools (especially SQL and python - see our full stack below). Strong commercial acumen, preferably in pricing, margin optimisation, and/or growth analytics. Proven experience mentoring and developing data professionals. Strong communication skills to influence non-technical stakeholders and senior leadership. A track record of delivering actionable insights that drive measurable business impact. Python, pandas and SQL in Jupyter notebooks for analysis dbt and Databricks data platform with Delta Lake Lightdash as our BI tool and semantic layer Streamlit for interactive data applications Airflow for orchestration CI/CD with GitHub and CircleCI Infrastructure on AWS, deployed with Terraform / Spacelift
Black Duck Software, Inc. helps organizations build secure, high-quality software, minimizing risks while maximizing speed and productivity. Black Duck, a recognized pioneer in application security, provides SAST, SCA, and DAST solutions that enable teams to quickly find and fix vulnerabilities and defects in proprietary code, open source components, and application behavior. With a combination of industry-leading tools, services, and expertise, only Black Duck helps organizations maximize security and quality in DevSecOps and throughout the software development life cycle. The Data Science group sits within Black Duck's Data Engineering organisation, operating as a centre of excellence in statistical analysis, machine learning engineering, and applied AI. We work at the intersection of cybersecurity and data intelligence; building models, evaluation frameworks, and AI-powered capabilities that directly shape how tens of thousands of developers and security teams understand and respond to risk. Our work spans predictive analytics, behavioural modelling, LLM integration, and the development of internal AI platforms. We're opinionated about quality, curious by default, and outcome-driven in everything we ship. Our Values Trust: We'd rather be late than wrong. Our work is only as valuable as its credibility. Collaboration: We have deep technical expertise, but we work shoulder-to-shoulder with the subject matter experts who define what "correct" actually means in our domain. Results: We're outcome-driven. Research has value, but it has more value when it's written up, shipped, or handed off. Curiosity: Exploration is core to what we do - including the dead ends. (It's not science unless you write it down.) Fun: We work in a genuinely strange corner of the data world. Revel in it. About the Role As a Senior Data Scientist, you will own the design, development, and production deployment of machine learning and AI systems that drive measurable outcomes across Black Duck's cybersecurity platforms. This is primarily a technical individual contributor role - we're looking for someone who can take a problem from framing through to a shipped, evaluated, production system, and who brings genuine depth in ML/AI engineering rather than general data work. Data infrastructure and pipeline ownership sits with our dedicated Data Engineering function. Your focus is on what we do with that data: building models, evaluating them rigorously, integrating AI capabilities into products and internal tooling, and helping shape how the team approaches applied AI at scale. The role is primarily based at our Belfast R&D site. UK/EMEA remote or hybrid applicants will be considered, with at least quarterly travel to Belfast expected. Additional conference and collaboration opportunities are available commensurate with your impact. Key Responsibilities Design, develop, and maintain machine learning and AI systems, from prototype through to production, with clear evaluation criteria and operational handover Lead the integration of LLM and agentic AI capabilities into Black Duck products and internal platforms (including prompt engineering, retrieval-augmented generation, and tool/agent orchestration) Design and own LLM evaluation frameworks: defining task specific metrics, building offline and online eval pipelines, running structured comparisons across models and configurations, and producing clear recommendations with supporting evidence Conduct cost benefit analysis on AI/ML system decisions: model / architecture / methodology selection, operational costs, build vs buy trade offs, and quantifying the value of AI/ML interventions against baseline approaches; communicating findings clearly to technical and non technical stakeholders Collaborate with R&D and Product Engineering to embed AI capabilities into existing workflows and surfaces Contribute to the team's shared practices around model governance, reproducibility, and responsible AI use Mentor team members, peers and the wider organisation on evolving and emerging ML/AI engineering practices and help continuously maintain the organisation's technical standards Key Qualifications 5+ years of hands on experience in data science, machine learning engineering, or applied AI - with demonstrable delivery of production ML/AI systems, not just research or analysis Strong Software engineering proficiency; you can design and deliver a project or module from scratch that others can build on Experience deploying ML/AI models in production on cloud infrastructure (AWS, Azure, or GCP) and/or Kubernetes workloads Practical experience with ML/AI development stacks: PyTorch, scikit learn, HuggingFace or equivalent; experiment tracking (MLflow, W&B or similar); and model evaluation tooling Experience designing and executing LLM evaluations: building eval datasets, defining metrics, running model comparisons, and translating results into actionable decisions Experience conducting cost benefit or trade off analysis on AI systems; weighing inference cost, latency, accuracy, and operational complexity against business or product value Familiarity with agentic AI patterns: tool use, multi step reasoning, agent orchestration (LangChain, LangGraph, or equivalent) Experience working with LLMs via API integration, prompt engineering, and RAG pipelines Experience with Jupyter and standard scientific Python (pandas, numpy, scipy) Ability to operate independently on multi month projects, manage your own priorities, and communicate clearly across engineering and non engineering stakeholders Hands on experience with AI assisted development tools (GitHub Copilot, Claude Code, Cursor, or similar) Nice to Have Degree in Computer Science, Data Science, Artificial Intelligence, Mathematics, Physics, or a related field (or demonstrated equivalent through portfolio and track record) Familiarity with cybersecurity concepts, application security testing, or software supply chain risk Experience with data/feature stores, model registries, or MLOps tooling (Airflow, DBT, Databricks, or equivalent) Familiarity with Data Mesh or Data Product concepts Experience with enterprise data visualisation (Power BI, Grafana, Snowflake, Databricks dashboards) Comfort in Linux/CLI environments and experience contributing to shared codebases (Git, code review, CI/CD) Track record of written or public communication: internal documentation, papers, blog posts, or conference contributions Black Duck is an equal opportunity employer. We consider all applicants for employment without regard to race, color, national origin, religion, sex, gender identity or expression, age, disability, sexual orientation, veteran or military service status, or any other characteristic protected by applicable law. Black Duck complies with all applicable laws prohibiting employment discrimination in every jurisdiction where it operates and provides reasonable accommodations to individuals with disabilities in accordance with applicable law.
19/07/2026
Full time
Black Duck Software, Inc. helps organizations build secure, high-quality software, minimizing risks while maximizing speed and productivity. Black Duck, a recognized pioneer in application security, provides SAST, SCA, and DAST solutions that enable teams to quickly find and fix vulnerabilities and defects in proprietary code, open source components, and application behavior. With a combination of industry-leading tools, services, and expertise, only Black Duck helps organizations maximize security and quality in DevSecOps and throughout the software development life cycle. The Data Science group sits within Black Duck's Data Engineering organisation, operating as a centre of excellence in statistical analysis, machine learning engineering, and applied AI. We work at the intersection of cybersecurity and data intelligence; building models, evaluation frameworks, and AI-powered capabilities that directly shape how tens of thousands of developers and security teams understand and respond to risk. Our work spans predictive analytics, behavioural modelling, LLM integration, and the development of internal AI platforms. We're opinionated about quality, curious by default, and outcome-driven in everything we ship. Our Values Trust: We'd rather be late than wrong. Our work is only as valuable as its credibility. Collaboration: We have deep technical expertise, but we work shoulder-to-shoulder with the subject matter experts who define what "correct" actually means in our domain. Results: We're outcome-driven. Research has value, but it has more value when it's written up, shipped, or handed off. Curiosity: Exploration is core to what we do - including the dead ends. (It's not science unless you write it down.) Fun: We work in a genuinely strange corner of the data world. Revel in it. About the Role As a Senior Data Scientist, you will own the design, development, and production deployment of machine learning and AI systems that drive measurable outcomes across Black Duck's cybersecurity platforms. This is primarily a technical individual contributor role - we're looking for someone who can take a problem from framing through to a shipped, evaluated, production system, and who brings genuine depth in ML/AI engineering rather than general data work. Data infrastructure and pipeline ownership sits with our dedicated Data Engineering function. Your focus is on what we do with that data: building models, evaluating them rigorously, integrating AI capabilities into products and internal tooling, and helping shape how the team approaches applied AI at scale. The role is primarily based at our Belfast R&D site. UK/EMEA remote or hybrid applicants will be considered, with at least quarterly travel to Belfast expected. Additional conference and collaboration opportunities are available commensurate with your impact. Key Responsibilities Design, develop, and maintain machine learning and AI systems, from prototype through to production, with clear evaluation criteria and operational handover Lead the integration of LLM and agentic AI capabilities into Black Duck products and internal platforms (including prompt engineering, retrieval-augmented generation, and tool/agent orchestration) Design and own LLM evaluation frameworks: defining task specific metrics, building offline and online eval pipelines, running structured comparisons across models and configurations, and producing clear recommendations with supporting evidence Conduct cost benefit analysis on AI/ML system decisions: model / architecture / methodology selection, operational costs, build vs buy trade offs, and quantifying the value of AI/ML interventions against baseline approaches; communicating findings clearly to technical and non technical stakeholders Collaborate with R&D and Product Engineering to embed AI capabilities into existing workflows and surfaces Contribute to the team's shared practices around model governance, reproducibility, and responsible AI use Mentor team members, peers and the wider organisation on evolving and emerging ML/AI engineering practices and help continuously maintain the organisation's technical standards Key Qualifications 5+ years of hands on experience in data science, machine learning engineering, or applied AI - with demonstrable delivery of production ML/AI systems, not just research or analysis Strong Software engineering proficiency; you can design and deliver a project or module from scratch that others can build on Experience deploying ML/AI models in production on cloud infrastructure (AWS, Azure, or GCP) and/or Kubernetes workloads Practical experience with ML/AI development stacks: PyTorch, scikit learn, HuggingFace or equivalent; experiment tracking (MLflow, W&B or similar); and model evaluation tooling Experience designing and executing LLM evaluations: building eval datasets, defining metrics, running model comparisons, and translating results into actionable decisions Experience conducting cost benefit or trade off analysis on AI systems; weighing inference cost, latency, accuracy, and operational complexity against business or product value Familiarity with agentic AI patterns: tool use, multi step reasoning, agent orchestration (LangChain, LangGraph, or equivalent) Experience working with LLMs via API integration, prompt engineering, and RAG pipelines Experience with Jupyter and standard scientific Python (pandas, numpy, scipy) Ability to operate independently on multi month projects, manage your own priorities, and communicate clearly across engineering and non engineering stakeholders Hands on experience with AI assisted development tools (GitHub Copilot, Claude Code, Cursor, or similar) Nice to Have Degree in Computer Science, Data Science, Artificial Intelligence, Mathematics, Physics, or a related field (or demonstrated equivalent through portfolio and track record) Familiarity with cybersecurity concepts, application security testing, or software supply chain risk Experience with data/feature stores, model registries, or MLOps tooling (Airflow, DBT, Databricks, or equivalent) Familiarity with Data Mesh or Data Product concepts Experience with enterprise data visualisation (Power BI, Grafana, Snowflake, Databricks dashboards) Comfort in Linux/CLI environments and experience contributing to shared codebases (Git, code review, CI/CD) Track record of written or public communication: internal documentation, papers, blog posts, or conference contributions Black Duck is an equal opportunity employer. We consider all applicants for employment without regard to race, color, national origin, religion, sex, gender identity or expression, age, disability, sexual orientation, veteran or military service status, or any other characteristic protected by applicable law. Black Duck complies with all applicable laws prohibiting employment discrimination in every jurisdiction where it operates and provides reasonable accommodations to individuals with disabilities in accordance with applicable law.
Manager, Tax Technology and Transformation, AI & Data, London Location: London Other locations: Primary Location Only Date: Jul 16, 2026 Requisition ID: At EY, we're all in to shape your future with confidence. We'll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help to build a better working world. The opportunity EY Tax is a market leader, renowned for delivering sustainable growth and empowering our people to sh0ape their own careers. Our diverse, collaborative team advises on high-profile transactions, combining tec0hnical expertise, innovation and a genuine focus on continuous development. Join us to work on chall0enging, multi-country projects in a supportive, dynamic environment where your impact truly matte0rs. Our Tax Technology and Transformation (TTT) team sits at the heart of EY's Financial Services Tax practice, helping banks, insurers and asset managers reinvent how their tax and finance functions operate. We combine data engineering, intelligent automation and artificial intelligence - from AI-ready data foundations to generative and agentic AI - to transform tax compliance, reporting and advisory. As a Manager, you will lead multi-disciplinary teams to deliver these solutions, own trusted client relationships, and help shape our AI and data propositions in one of the fastest-moving areas of the market. Your key responsibilities Lead the end-to-end delivery of AI and data engagements for financial services tax clients - scoping requirements, shaping the solution design, and managing delivery to time, budget and quality. Act as a day-to-day client lead and trusted adviser, translating complex tax, data and AI concepts into clear business value for both technical and non-technical stakeholders. Design and oversee AI-enabled and data-driven tax solutions - including generative and agentic AI use cases, data pipelines and models - ensuring they are robust, well-governed and ready for production. Manage, coach and review the work of Seniors, analysts and interns, building AI and data capability across the team. Support business development - shaping propositions, contributing to proposals and demonstrations, and identifying opportunities to grow existing accounts. Champion responsible AI, data governance and quality standards, staying abreast of developments in AI, tax technology and regulation and translating them into practical action. Skills and attributes for success What we look for Demonstrated proficiency in: Rapid prototyping of data science and machine learning solutions on large datasets. Building agentic workflows and autonomous agents using frameworks like Langchain, Semantic Kernel, AutoGen, and LangGraph. Developing and optimizing generative AI models, focusing on prompt engineering and LLMs. Writing production-grade Python applications. Managing version control with Git and using Docker for containerization. Knowledge of Databricks. Excellent communication skills, with the ability to effectively convey complex concepts to cross-functional teams and stakeholders. Experience in Agile development environment and familiar with Agile ceremonies (e.g. stand-up, backlog refinement, sprint planning) Ability to thrive in fast-paced environments, and a thoughtful approach to AI fairness, accountability, and transparency. Ideally, you'll also have Knowledge of financial services tax or regulatory reporting, or of enterprise tax technology (for example Alteryx, the Microsoft Power Platform or Microsoft Fabric). Recognised cloud, data or AI certifications (for example Azure, AWS, Databricks or a generative-AI credential), or a track record of proposition and business development.
19/07/2026
Full time
Manager, Tax Technology and Transformation, AI & Data, London Location: London Other locations: Primary Location Only Date: Jul 16, 2026 Requisition ID: At EY, we're all in to shape your future with confidence. We'll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help to build a better working world. The opportunity EY Tax is a market leader, renowned for delivering sustainable growth and empowering our people to sh0ape their own careers. Our diverse, collaborative team advises on high-profile transactions, combining tec0hnical expertise, innovation and a genuine focus on continuous development. Join us to work on chall0enging, multi-country projects in a supportive, dynamic environment where your impact truly matte0rs. Our Tax Technology and Transformation (TTT) team sits at the heart of EY's Financial Services Tax practice, helping banks, insurers and asset managers reinvent how their tax and finance functions operate. We combine data engineering, intelligent automation and artificial intelligence - from AI-ready data foundations to generative and agentic AI - to transform tax compliance, reporting and advisory. As a Manager, you will lead multi-disciplinary teams to deliver these solutions, own trusted client relationships, and help shape our AI and data propositions in one of the fastest-moving areas of the market. Your key responsibilities Lead the end-to-end delivery of AI and data engagements for financial services tax clients - scoping requirements, shaping the solution design, and managing delivery to time, budget and quality. Act as a day-to-day client lead and trusted adviser, translating complex tax, data and AI concepts into clear business value for both technical and non-technical stakeholders. Design and oversee AI-enabled and data-driven tax solutions - including generative and agentic AI use cases, data pipelines and models - ensuring they are robust, well-governed and ready for production. Manage, coach and review the work of Seniors, analysts and interns, building AI and data capability across the team. Support business development - shaping propositions, contributing to proposals and demonstrations, and identifying opportunities to grow existing accounts. Champion responsible AI, data governance and quality standards, staying abreast of developments in AI, tax technology and regulation and translating them into practical action. Skills and attributes for success What we look for Demonstrated proficiency in: Rapid prototyping of data science and machine learning solutions on large datasets. Building agentic workflows and autonomous agents using frameworks like Langchain, Semantic Kernel, AutoGen, and LangGraph. Developing and optimizing generative AI models, focusing on prompt engineering and LLMs. Writing production-grade Python applications. Managing version control with Git and using Docker for containerization. Knowledge of Databricks. Excellent communication skills, with the ability to effectively convey complex concepts to cross-functional teams and stakeholders. Experience in Agile development environment and familiar with Agile ceremonies (e.g. stand-up, backlog refinement, sprint planning) Ability to thrive in fast-paced environments, and a thoughtful approach to AI fairness, accountability, and transparency. Ideally, you'll also have Knowledge of financial services tax or regulatory reporting, or of enterprise tax technology (for example Alteryx, the Microsoft Power Platform or Microsoft Fabric). Recognised cloud, data or AI certifications (for example Azure, AWS, Databricks or a generative-AI credential), or a track record of proposition and business development.
Join us at Barclays as a Senior Data Platform Developer. At Barclays, we're shaping the future of banking through cutting edge technology and data innovation. We are looking for a highly skilled Senior Data Platform Developer to join our growing team, where you'll play a key role in building and enhancing scalable, cloud based data platforms that power critical business decisions. Essential Skills Strong expertise in AWS (core services for data and platform engineering) Advanced proficiency in PySpark for distributed data processing Solid programming experience in Python Experience building and maintaining large scale data platforms Desirable Skills Experience with CI/CD pipelines and DevOps practices Strong understanding of data modelling concepts (e.g., dimensional modelling) Experience working with Databricks or similar modern data platforms This role is based in Glasgow. Purpose of the role To design, develop and improve software, utilising various engineering methodologies, that provides business, platform, and technology capabilities for our customers and colleagues. Accountabilities Development and delivery of high quality software solutions by using industry aligned programming languages, frameworks, and tools. Ensuring that code is scalable, maintainable, and optimised for performance. Cross functional collaboration with product managers, designers, and other engineers to define software requirements, devise solution strategies, and ensure seamless integration and alignment with business objectives. Collaboration with peers, participation in code reviews, and promoting a culture of code quality and knowledge sharing. Stay informed of industry technology trends and innovations and actively contribute to the organisation's technology communities to foster a culture of technical excellence and growth. Adherence to secure coding practices to mitigate vulnerabilities, protect sensitive data, and ensure secure software solutions. Implementation of effective unit testing practices to ensure proper code design, readability, and reliability. Assistant Vice President Expectations To advise and influence decision making, contribute to policy development and take responsibility for operational effectiveness. Collaborate closely with other functions/ business divisions. Lead a team performing complex tasks, using well developed professional knowledge and skills to deliver on work that impacts the whole business function. Set objectives and coach employees in pursuit of those objectives, appraisal of performance relative to objectives and determination of reward outcomes. If the position has leadership responsibilities, People Leaders are expected to demonstrate a clear set of leadership behaviours to create an environment for colleagues to thrive and deliver to a consistently excellent standard. The four LEAD behaviours are: L - Listen and be authentic, E - Energise and inspire, A - Align across the enterprise, D - Develop others. OR for an individual contributor, they will lead collaborative assignments and guide team members through structured assignments, identify the need for the inclusion of other areas of specialisation to complete assignments. They will identify new directions for assignments and/ or projects, identifying a combination of cross functional methodologies or practices to meet required outcomes. Consult on complex issues; providing advice to People Leaders to support the resolution of escalated issues. Identify ways to mitigate risk and developing new policies/procedures in support of the control and governance agenda. Take ownership for managing risk and strengthening controls in relation to the work done. Perform work that is closely related to that of other areas, which requires understanding of how areas coordinate and contribute to the achievement of the objectives of the organisation sub function. Collaborate with other areas of work, for business aligned support areas to keep up to speed with business activity and the business strategy. Engage in complex analysis of data from multiple sources of information, internal and external sources such as procedures and practises (in other areas, teams, companies, etc).to solve problems creatively and effectively. Communicate complex information. 'Complex' information could include sensitive information or information that is difficult to communicate because of its content or its audience. Influence or convince stakeholders to achieve outcomes. All colleagues will be expected to demonstrate the Barclays Values of Respect, Integrity, Service, Excellence and Stewardship - our moral compass, helping us do what we believe is right. They will also be expected to demonstrate the Barclays Mindset - to Empower, Challenge and Drive - the operating manual for how we behave.
19/07/2026
Full time
Join us at Barclays as a Senior Data Platform Developer. At Barclays, we're shaping the future of banking through cutting edge technology and data innovation. We are looking for a highly skilled Senior Data Platform Developer to join our growing team, where you'll play a key role in building and enhancing scalable, cloud based data platforms that power critical business decisions. Essential Skills Strong expertise in AWS (core services for data and platform engineering) Advanced proficiency in PySpark for distributed data processing Solid programming experience in Python Experience building and maintaining large scale data platforms Desirable Skills Experience with CI/CD pipelines and DevOps practices Strong understanding of data modelling concepts (e.g., dimensional modelling) Experience working with Databricks or similar modern data platforms This role is based in Glasgow. Purpose of the role To design, develop and improve software, utilising various engineering methodologies, that provides business, platform, and technology capabilities for our customers and colleagues. Accountabilities Development and delivery of high quality software solutions by using industry aligned programming languages, frameworks, and tools. Ensuring that code is scalable, maintainable, and optimised for performance. Cross functional collaboration with product managers, designers, and other engineers to define software requirements, devise solution strategies, and ensure seamless integration and alignment with business objectives. Collaboration with peers, participation in code reviews, and promoting a culture of code quality and knowledge sharing. Stay informed of industry technology trends and innovations and actively contribute to the organisation's technology communities to foster a culture of technical excellence and growth. Adherence to secure coding practices to mitigate vulnerabilities, protect sensitive data, and ensure secure software solutions. Implementation of effective unit testing practices to ensure proper code design, readability, and reliability. Assistant Vice President Expectations To advise and influence decision making, contribute to policy development and take responsibility for operational effectiveness. Collaborate closely with other functions/ business divisions. Lead a team performing complex tasks, using well developed professional knowledge and skills to deliver on work that impacts the whole business function. Set objectives and coach employees in pursuit of those objectives, appraisal of performance relative to objectives and determination of reward outcomes. If the position has leadership responsibilities, People Leaders are expected to demonstrate a clear set of leadership behaviours to create an environment for colleagues to thrive and deliver to a consistently excellent standard. The four LEAD behaviours are: L - Listen and be authentic, E - Energise and inspire, A - Align across the enterprise, D - Develop others. OR for an individual contributor, they will lead collaborative assignments and guide team members through structured assignments, identify the need for the inclusion of other areas of specialisation to complete assignments. They will identify new directions for assignments and/ or projects, identifying a combination of cross functional methodologies or practices to meet required outcomes. Consult on complex issues; providing advice to People Leaders to support the resolution of escalated issues. Identify ways to mitigate risk and developing new policies/procedures in support of the control and governance agenda. Take ownership for managing risk and strengthening controls in relation to the work done. Perform work that is closely related to that of other areas, which requires understanding of how areas coordinate and contribute to the achievement of the objectives of the organisation sub function. Collaborate with other areas of work, for business aligned support areas to keep up to speed with business activity and the business strategy. Engage in complex analysis of data from multiple sources of information, internal and external sources such as procedures and practises (in other areas, teams, companies, etc).to solve problems creatively and effectively. Communicate complex information. 'Complex' information could include sensitive information or information that is difficult to communicate because of its content or its audience. Influence or convince stakeholders to achieve outcomes. All colleagues will be expected to demonstrate the Barclays Values of Respect, Integrity, Service, Excellence and Stewardship - our moral compass, helping us do what we believe is right. They will also be expected to demonstrate the Barclays Mindset - to Empower, Challenge and Drive - the operating manual for how we behave.
Responsibilities Owns the data modelling strategy, sets standards for data modelling, transformations, and governance. Leads the design and implementation of new features, such as the creation of a new star schema and other best practices to optimise data usability. Sets best practices and standards on how we use SQL, dbt, Python, PySpark and/or other languages to solve business problems. Becomes an expert in the business subject area the team is working on, holding expertise on both the business requirements as well as the technical implementation. Delivers high quality code, provides technical mentorship, and ensures the team is building scalable, maintainable data models. Co-owns the backlog with the Engineering Manager and helps to break down technical requirements. Requirements Extensive experience in SQL / Python / PySpark and/or other languages relevant to data processing Extensive experience in dbt and ideally Airflow (or other orchestration tools) Extensive experience in Entity-Relationship modelling and Dimensional modelling Experience with Cloud Data Warehousing (eg Snowflake, Databricks or BigQuery) and Cloud (AWS, GCP or Azure) Familiarity with Tableau Excellent communication and problem solving skills and the ability to translate business requirements into technical requirements Able to architect custom AI solutions and smart automated systems that are safe, maintainable, and aligned with our long-term mission Act as a technical bridge and mentor, training "builders" across the company to move from basic AI usage to sophisticated system creation ATS Optimization Keywords Below are skills and terms extracted directly from this job posting to improve Applicant Tracking System (ATS) visibility. This unique feature helps candidates tailor their applications more effectively - a feature exclusive to JobTailor job listings. Hard Skills SQL Python PySpark Dbt Entity-Relationship Modelling Dimensional Modelling Cloud Data Warehousing Airflow Data Transformations Data Governance Soft Skills Excellent Communication Problem Solving Technical Mentorship
19/07/2026
Full time
Responsibilities Owns the data modelling strategy, sets standards for data modelling, transformations, and governance. Leads the design and implementation of new features, such as the creation of a new star schema and other best practices to optimise data usability. Sets best practices and standards on how we use SQL, dbt, Python, PySpark and/or other languages to solve business problems. Becomes an expert in the business subject area the team is working on, holding expertise on both the business requirements as well as the technical implementation. Delivers high quality code, provides technical mentorship, and ensures the team is building scalable, maintainable data models. Co-owns the backlog with the Engineering Manager and helps to break down technical requirements. Requirements Extensive experience in SQL / Python / PySpark and/or other languages relevant to data processing Extensive experience in dbt and ideally Airflow (or other orchestration tools) Extensive experience in Entity-Relationship modelling and Dimensional modelling Experience with Cloud Data Warehousing (eg Snowflake, Databricks or BigQuery) and Cloud (AWS, GCP or Azure) Familiarity with Tableau Excellent communication and problem solving skills and the ability to translate business requirements into technical requirements Able to architect custom AI solutions and smart automated systems that are safe, maintainable, and aligned with our long-term mission Act as a technical bridge and mentor, training "builders" across the company to move from basic AI usage to sophisticated system creation ATS Optimization Keywords Below are skills and terms extracted directly from this job posting to improve Applicant Tracking System (ATS) visibility. This unique feature helps candidates tailor their applications more effectively - a feature exclusive to JobTailor job listings. Hard Skills SQL Python PySpark Dbt Entity-Relationship Modelling Dimensional Modelling Cloud Data Warehousing Airflow Data Transformations Data Governance Soft Skills Excellent Communication Problem Solving Technical Mentorship
Elevate your career by steering multi-faceted technology programs, integrating innovative solutions, and driving impact across global operations. The Chief Data & Analytics Office (CDAO) at JPMorganChase is responsible for accelerating the firm's data and analytics journey. This includes ensuring the quality, integrity, and security of the firm's data, as well as leveraging it to generate insights and drive decision-making. The CDAO also develops and implements solutions that support the firm's commercial goals by responsibly harnessing artificial intelligence and machine learning to develop new products, improve productivity, and enhance risk management. As a Lead Technical Program Manager at JPMorganChase within CDAO, you will lead complex, cross-functional technology programs that impact experiences across the firm, including clients, employees, and stakeholders. You will use strong analytical reasoning and adaptability to break down business, technical, and operational objectives into manageable workstreams, navigate ambiguity, and drive change. With demonstrated technical fluency, you will manage resources, budgets, and cross-functional teams to deliver innovative solutions aligned to strategic goals. Your exceptional communication and influencing skills will foster productive stakeholder relationships, ensuring alignment and effective risk management. In this pivotal role, you will also contribute to new policies and processes that shape the future of our technology landscape. Job responsibilities Create and maintain detailed project plans, timelines, and delivery schedules for assigned programs Manage day-to-day program execution using JIRA, Confluence, and other project management tools, ensuring accurate tracking of user stories, epics, and sprint progress Facilitate agile ceremonies, including sprint planning, daily standups, retrospectives, and backlog grooming, with engineering teams Maintain comprehensive program documentation, including status reports, risk registers, RAID logs, and dependency matrices Oversee engineering risks, issues, and dependencies across assigned programs Engage stakeholders, including customers and partners across Lines of Business (LOBs) Guide the selection and implementation of appropriate technologies, platforms, and software tools, leveraging technical fluency Champion continuous improvement by identifying process optimization opportunities, incorporating best practices, and staying abreast of emerging technologies Partner with Product to drive business outcomes, ensuring technical programs align with strategic goals Prepare and deliver regular status updates and presentations to stakeholders and leadership, communicating progress, risks, and blockers Required qualifications, capabilities, and skills 5+ years of experience (or equivalent expertise) in technical program management, leading complex technology initiatives in large organizations Hands-on experience with agile delivery tools (JIRA, Confluence) and planning tools (e.g., MS Project), with proven ability to maintain accurate program artifacts and metrics Demonstrated proficiency in technical solutioning, vendor product evaluation, vendor management, and solution implementation Strong analytical reasoning skills, applying critical thinking and problem-solving techniques to break down business, technical, and operational objectives Proven ability to lead through change, manage dependencies, and control scope in high-pressure, shifting environments Strong stakeholder management skills, building productive relationships and driving outcomes aligned with firm objectives Understanding of data platform trade-offs, including performance optimization, cost management, scalability, and operational excellence Deep technical understanding of modern data platform architectures, including data lakes, data warehouses, Lakehouse architectures, and distributed computing frameworks Experience with enterprise-scale implementations of cloud-native data platforms such as Databricks and Snowflake Good understanding of AWS data analytics services, including Redshift, EMR, Glue, Athena, Kinesis, Lake Formation, MSK, and S3 data lake patterns, with demonstrated experience architecting end-to-end data solutions Experience navigating complex data governance, security, and compliance requirements across multi-cloud and hybrid data environments at enterprise scale
19/07/2026
Full time
Elevate your career by steering multi-faceted technology programs, integrating innovative solutions, and driving impact across global operations. The Chief Data & Analytics Office (CDAO) at JPMorganChase is responsible for accelerating the firm's data and analytics journey. This includes ensuring the quality, integrity, and security of the firm's data, as well as leveraging it to generate insights and drive decision-making. The CDAO also develops and implements solutions that support the firm's commercial goals by responsibly harnessing artificial intelligence and machine learning to develop new products, improve productivity, and enhance risk management. As a Lead Technical Program Manager at JPMorganChase within CDAO, you will lead complex, cross-functional technology programs that impact experiences across the firm, including clients, employees, and stakeholders. You will use strong analytical reasoning and adaptability to break down business, technical, and operational objectives into manageable workstreams, navigate ambiguity, and drive change. With demonstrated technical fluency, you will manage resources, budgets, and cross-functional teams to deliver innovative solutions aligned to strategic goals. Your exceptional communication and influencing skills will foster productive stakeholder relationships, ensuring alignment and effective risk management. In this pivotal role, you will also contribute to new policies and processes that shape the future of our technology landscape. Job responsibilities Create and maintain detailed project plans, timelines, and delivery schedules for assigned programs Manage day-to-day program execution using JIRA, Confluence, and other project management tools, ensuring accurate tracking of user stories, epics, and sprint progress Facilitate agile ceremonies, including sprint planning, daily standups, retrospectives, and backlog grooming, with engineering teams Maintain comprehensive program documentation, including status reports, risk registers, RAID logs, and dependency matrices Oversee engineering risks, issues, and dependencies across assigned programs Engage stakeholders, including customers and partners across Lines of Business (LOBs) Guide the selection and implementation of appropriate technologies, platforms, and software tools, leveraging technical fluency Champion continuous improvement by identifying process optimization opportunities, incorporating best practices, and staying abreast of emerging technologies Partner with Product to drive business outcomes, ensuring technical programs align with strategic goals Prepare and deliver regular status updates and presentations to stakeholders and leadership, communicating progress, risks, and blockers Required qualifications, capabilities, and skills 5+ years of experience (or equivalent expertise) in technical program management, leading complex technology initiatives in large organizations Hands-on experience with agile delivery tools (JIRA, Confluence) and planning tools (e.g., MS Project), with proven ability to maintain accurate program artifacts and metrics Demonstrated proficiency in technical solutioning, vendor product evaluation, vendor management, and solution implementation Strong analytical reasoning skills, applying critical thinking and problem-solving techniques to break down business, technical, and operational objectives Proven ability to lead through change, manage dependencies, and control scope in high-pressure, shifting environments Strong stakeholder management skills, building productive relationships and driving outcomes aligned with firm objectives Understanding of data platform trade-offs, including performance optimization, cost management, scalability, and operational excellence Deep technical understanding of modern data platform architectures, including data lakes, data warehouses, Lakehouse architectures, and distributed computing frameworks Experience with enterprise-scale implementations of cloud-native data platforms such as Databricks and Snowflake Good understanding of AWS data analytics services, including Redshift, EMR, Glue, Athena, Kinesis, Lake Formation, MSK, and S3 data lake patterns, with demonstrated experience architecting end-to-end data solutions Experience navigating complex data governance, security, and compliance requirements across multi-cloud and hybrid data environments at enterprise scale
Senior Databricks Architect Technology: Databricks (Spark, PySpark/SQL) and data lake architectures. Location: London, UK. Compensation: Competitive (including bonus). Job Description We are looking for a Data Architect to design, build, and operate scalable data pipelines and data products, enabling a modern data mesh architecture. The role focuses on integrating legacy systems with cloud-native platforms to support analytics, reporting, and domain-owned data products. Primary Skills Strong experience with Databricks (Spark, PySpark/SQL) and data lake architectures. Hands on experience with streaming technologies, especially Kafka / Confluent Kafka. Experience integrating legacy data sources such as DB2 (mainframe) and SQL Server. Working knowledge of AWS data services, especially S3. Understanding of data product thinking, data mesh concepts, and modern data engineering best practices. Key Responsibilities Build and maintain batch and streaming data pipelines from legacy mainframe DB2 and on prem SQL Server systems into an AWS based data lake. Implement real time ingestion using Confluent Kafka and land data in Amazon S3. Develop data transformations and analytics pipelines in Databricks using the medallion architecture (Bronze, Silver, Gold). Design and deliver high quality, reusable data products aligned to data mesh principles. Ensure data quality, reliability, security, and governance across pipelines. Collaborate with domain teams, platform teams, and stakeholders to enable self serve analytics and consumption. Good to Have Experience in banking or financial services data platforms. Familiarity with data governance, metadata management, and regulatory reporting. Personal Qualities High analytical skills. A high degree of initiative and flexibility. High customer orientation. High quality awareness. Excellent verbal and written communication skills. Facts of employment at Infosys are based on merit, competence and performance. Infosys is proud to be an equal opportunity employer.
19/07/2026
Full time
Senior Databricks Architect Technology: Databricks (Spark, PySpark/SQL) and data lake architectures. Location: London, UK. Compensation: Competitive (including bonus). Job Description We are looking for a Data Architect to design, build, and operate scalable data pipelines and data products, enabling a modern data mesh architecture. The role focuses on integrating legacy systems with cloud-native platforms to support analytics, reporting, and domain-owned data products. Primary Skills Strong experience with Databricks (Spark, PySpark/SQL) and data lake architectures. Hands on experience with streaming technologies, especially Kafka / Confluent Kafka. Experience integrating legacy data sources such as DB2 (mainframe) and SQL Server. Working knowledge of AWS data services, especially S3. Understanding of data product thinking, data mesh concepts, and modern data engineering best practices. Key Responsibilities Build and maintain batch and streaming data pipelines from legacy mainframe DB2 and on prem SQL Server systems into an AWS based data lake. Implement real time ingestion using Confluent Kafka and land data in Amazon S3. Develop data transformations and analytics pipelines in Databricks using the medallion architecture (Bronze, Silver, Gold). Design and deliver high quality, reusable data products aligned to data mesh principles. Ensure data quality, reliability, security, and governance across pipelines. Collaborate with domain teams, platform teams, and stakeholders to enable self serve analytics and consumption. Good to Have Experience in banking or financial services data platforms. Familiarity with data governance, metadata management, and regulatory reporting. Personal Qualities High analytical skills. A high degree of initiative and flexibility. High customer orientation. High quality awareness. Excellent verbal and written communication skills. Facts of employment at Infosys are based on merit, competence and performance. Infosys is proud to be an equal opportunity employer.
AI Solution Architects & Technical AI Leaders Scotland Hybrid We're supporting a major consulting and technology organization delivering enterprise AI and data transformation programmes across Financial Services. The focus is designing scalable AI architectures that move beyond proof of concept into secure, production-grade deployment across banking environments. Hiring across multiple levels, from Solution Architects through to senior technical leadership. What you'll be doing Designing AI and GenAI architecture strategies and roadmaps Building scalable AI/ML and Agentic AI platforms Working across LLMs, RAG, embeddings and semantic search Supporting AI deployment, governance and integration patterns Collaboration with engineering, data, DevOps and business teams Advising clients on AI platform capability and implementation strategy Environment Python LLMs, prompt engineering, fine-tuning, RAG LangChain, LangGraph, Agent frameworks Vector databases and semantic search MLOps and LLMOps AWS, Azure, GCP, Databricks Containerisation, Kubernetes and GPU infrastructure Requirements Experience designing enterprise AI or ML architectures Strong understanding of cloud and modern data platforms Exposure to scalable AI deployment and integration patterns Financial Services or regulated industry experience essential Strong stakeholder engagement and communication skills Open to candidates from Manager through to Associate Director level.
19/07/2026
Full time
AI Solution Architects & Technical AI Leaders Scotland Hybrid We're supporting a major consulting and technology organization delivering enterprise AI and data transformation programmes across Financial Services. The focus is designing scalable AI architectures that move beyond proof of concept into secure, production-grade deployment across banking environments. Hiring across multiple levels, from Solution Architects through to senior technical leadership. What you'll be doing Designing AI and GenAI architecture strategies and roadmaps Building scalable AI/ML and Agentic AI platforms Working across LLMs, RAG, embeddings and semantic search Supporting AI deployment, governance and integration patterns Collaboration with engineering, data, DevOps and business teams Advising clients on AI platform capability and implementation strategy Environment Python LLMs, prompt engineering, fine-tuning, RAG LangChain, LangGraph, Agent frameworks Vector databases and semantic search MLOps and LLMOps AWS, Azure, GCP, Databricks Containerisation, Kubernetes and GPU infrastructure Requirements Experience designing enterprise AI or ML architectures Strong understanding of cloud and modern data platforms Exposure to scalable AI deployment and integration patterns Financial Services or regulated industry experience essential Strong stakeholder engagement and communication skills Open to candidates from Manager through to Associate Director level.
AI Engineers & Technical AI Leaders Scotland Hybrid We're supporting a major consulting and technology organisation delivering AI and data transformation programmes across Financial Services and Banking. The focus is applied AI engineering, building production grade AI solutions across banking, risk, fraud, automation and enterprise platforms. Hiring across multiple levels, from Engineers through to senior technical leadership. What you'll be doing Building AI-enabled platforms and intelligent workflows Working with LLMs, RAG pipelines and embedding models Developing scalable backend services and AI integrations Collaborating across engineering, architecture and business teams Supporting AI deployment, governance and operational rollout Environment Python, SQL LLMs, prompt engineering, fine-tuning, RAG LangChain, LangGraph, Agent frameworks Vector databases, FastAPI, APIs AWS, Azure, GCP or Databricks CI/CD, MLOps and LLMOps Requirements Strong software or data engineering foundations Experience delivering AI or AI-enabled solutions Exposure to cloud and modern data platforms Financial Services or regulated industry experience essential Strong communication and stakeholder skills Open to candidates from Engineer through to Senior Manager level.
19/07/2026
Full time
AI Engineers & Technical AI Leaders Scotland Hybrid We're supporting a major consulting and technology organisation delivering AI and data transformation programmes across Financial Services and Banking. The focus is applied AI engineering, building production grade AI solutions across banking, risk, fraud, automation and enterprise platforms. Hiring across multiple levels, from Engineers through to senior technical leadership. What you'll be doing Building AI-enabled platforms and intelligent workflows Working with LLMs, RAG pipelines and embedding models Developing scalable backend services and AI integrations Collaborating across engineering, architecture and business teams Supporting AI deployment, governance and operational rollout Environment Python, SQL LLMs, prompt engineering, fine-tuning, RAG LangChain, LangGraph, Agent frameworks Vector databases, FastAPI, APIs AWS, Azure, GCP or Databricks CI/CD, MLOps and LLMOps Requirements Strong software or data engineering foundations Experience delivering AI or AI-enabled solutions Exposure to cloud and modern data platforms Financial Services or regulated industry experience essential Strong communication and stakeholder skills Open to candidates from Engineer through to Senior Manager level.
AI Engineers & Technical AI Leaders Manchester Hybrid We're supporting a major consulting and technology organisation delivering AI and data transformation programmes across Financial Services and Banking. The focus is applied AI engineering, building production grade AI solutions across banking, risk, fraud, automation and enterprise platforms. Hiring across multiple levels, from Engineers through to senior technical leadership. What you'll be doing Building AI-enabled platforms and intelligent workflows Working with LLMs, RAG pipelines and embedding models Developing scalable backend services and AI integrations Collaborating across engineering, architecture and business teams Supporting AI deployment, governance and operational rollout Environment Python, SQL LLMs, prompt engineering, fine-tuning, RAG LangChain, LangGraph, Agent frameworks Vector databases, FastAPI, APIs AWS, Azure, GCP or Databricks CI/CD, MLOps and LLMOps Requirements Strong software or data engineering foundations Experience delivering AI or AI-enabled solutions Exposure to cloud and modern data platforms Financial Services or regulated industry experience essential Strong communication and stakeholder skills Open to candidates from Engineer through to Senior Manager level.
19/07/2026
Full time
AI Engineers & Technical AI Leaders Manchester Hybrid We're supporting a major consulting and technology organisation delivering AI and data transformation programmes across Financial Services and Banking. The focus is applied AI engineering, building production grade AI solutions across banking, risk, fraud, automation and enterprise platforms. Hiring across multiple levels, from Engineers through to senior technical leadership. What you'll be doing Building AI-enabled platforms and intelligent workflows Working with LLMs, RAG pipelines and embedding models Developing scalable backend services and AI integrations Collaborating across engineering, architecture and business teams Supporting AI deployment, governance and operational rollout Environment Python, SQL LLMs, prompt engineering, fine-tuning, RAG LangChain, LangGraph, Agent frameworks Vector databases, FastAPI, APIs AWS, Azure, GCP or Databricks CI/CD, MLOps and LLMOps Requirements Strong software or data engineering foundations Experience delivering AI or AI-enabled solutions Exposure to cloud and modern data platforms Financial Services or regulated industry experience essential Strong communication and stakeholder skills Open to candidates from Engineer through to Senior Manager level.
Job Title: Senior Data Engineer Target Start Date: 20th June 2026 Contract Type: Permanent, Part Time, Full Time, Job Share option available Salary Range: £54,000- £81,000 Location: Eastleigh and Reigate Closing Date for applications: 18th April Senior Data Engineer: We are currently recruiting for a Senior Data Engineer to join our innovative Data team. You will join a collaborative team of data and AI engineers, scientists, developers, analysts, and architects. Together, we design and build modern machine learning and AI services that support analytics and improve products across the business. Main Responsibilities Build and support data products within our modern data platform Design and deliver solutions with engineers, scientists and product teams Develop and optimise data pipelines across the analytics platform Integrate data from varied sources with strong quality standards Maintain orchestration, monitoring and performance of data components Improve engineering processes across the wider data community Promote high coding and data practice standards Experiment with emerging data, ML and AI technologies Partner with architects on data product designs Work collaboratively in multi-functional agile squads Support ML and GenAI infrastructure and workflows Skills and Experience Passion for building scalable, resilient cloud data platforms Strong experience with Databricks or Snowflake on AWS Proven Python skills, including Spark and Airflow expertise Advanced SQL skills and end to end data modelling experience Experience building batch and real-time data integrations Hands on CICD skills with Git, Jenkins or similar Ability to ingest, cleanse and structure large, diverse datasets Knowledge of Terraform or similar IaC tools Experience with Docker and Kubernetes is beneficial Exposure to production Generative AI is an advantage Strong collaboration skills and a proactive attitude Benefits Flexible working - Smart Working within the UK and work day flexibility. Part time/Job share options. Minimum 35 days holiday (including bank holidays) with option to buy/sell days. Health benefits - Dental insurance, Health Cash Plan, Health screening, Will Writing, Voluntary Critical Illness, Mental Health First Aiders, Well being activities - mindfulness. Wealth benefits - 50% off motor and home insurance, Annual Bonus Schemes, Annual Salary Reviews, Competitive Pension, Employee Savings, Employee Loans. Work life - Well being activities, mindfulness sessions, Sports and Social Club events. Family support - Maternity/pregnant parent/primary adopter entitlement of 16 weeks at full pay and paternity/non pregnant parent/co adopter at 8 weeks' full pay. Benefits for them - Partner Life Assurance and Critical Illness cover. Tech deals - Deals on gadgets including wearables, tablets, laptops. Getting around - Car Salary Exchange, Cycle Scheme, Vehicle Breakdown Cover. Back to work - Return to work programme after maternity leave. Equal Opportunity We are an inclusive employer, encouraging anyone to apply. We are a signatory of Race at Work Charter, Women in Finance Charter, and member of iCAN, GAIN. We are a Disability Confident Leader and provide support and adjustments during recruitment.
19/07/2026
Full time
Job Title: Senior Data Engineer Target Start Date: 20th June 2026 Contract Type: Permanent, Part Time, Full Time, Job Share option available Salary Range: £54,000- £81,000 Location: Eastleigh and Reigate Closing Date for applications: 18th April Senior Data Engineer: We are currently recruiting for a Senior Data Engineer to join our innovative Data team. You will join a collaborative team of data and AI engineers, scientists, developers, analysts, and architects. Together, we design and build modern machine learning and AI services that support analytics and improve products across the business. Main Responsibilities Build and support data products within our modern data platform Design and deliver solutions with engineers, scientists and product teams Develop and optimise data pipelines across the analytics platform Integrate data from varied sources with strong quality standards Maintain orchestration, monitoring and performance of data components Improve engineering processes across the wider data community Promote high coding and data practice standards Experiment with emerging data, ML and AI technologies Partner with architects on data product designs Work collaboratively in multi-functional agile squads Support ML and GenAI infrastructure and workflows Skills and Experience Passion for building scalable, resilient cloud data platforms Strong experience with Databricks or Snowflake on AWS Proven Python skills, including Spark and Airflow expertise Advanced SQL skills and end to end data modelling experience Experience building batch and real-time data integrations Hands on CICD skills with Git, Jenkins or similar Ability to ingest, cleanse and structure large, diverse datasets Knowledge of Terraform or similar IaC tools Experience with Docker and Kubernetes is beneficial Exposure to production Generative AI is an advantage Strong collaboration skills and a proactive attitude Benefits Flexible working - Smart Working within the UK and work day flexibility. Part time/Job share options. Minimum 35 days holiday (including bank holidays) with option to buy/sell days. Health benefits - Dental insurance, Health Cash Plan, Health screening, Will Writing, Voluntary Critical Illness, Mental Health First Aiders, Well being activities - mindfulness. Wealth benefits - 50% off motor and home insurance, Annual Bonus Schemes, Annual Salary Reviews, Competitive Pension, Employee Savings, Employee Loans. Work life - Well being activities, mindfulness sessions, Sports and Social Club events. Family support - Maternity/pregnant parent/primary adopter entitlement of 16 weeks at full pay and paternity/non pregnant parent/co adopter at 8 weeks' full pay. Benefits for them - Partner Life Assurance and Critical Illness cover. Tech deals - Deals on gadgets including wearables, tablets, laptops. Getting around - Car Salary Exchange, Cycle Scheme, Vehicle Breakdown Cover. Back to work - Return to work programme after maternity leave. Equal Opportunity We are an inclusive employer, encouraging anyone to apply. We are a signatory of Race at Work Charter, Women in Finance Charter, and member of iCAN, GAIN. We are a Disability Confident Leader and provide support and adjustments during recruitment.
AI Solution Architects & Technical AI Leaders Manchester Hybrid We're supporting a major consulting and technology organisation delivering enterprise AI and data transformation programmes across Financial Services. The focus is designing scalable AI architectures that move beyond proof of concept into secure, production-grade deployment across banking environments. Hiring across multiple levels, from Solution Architects through to senior technical leadership. What you'll be doing Designing AI and GenAI architecture strategies and roadmaps Building scalable AI/ML and Agentic AI platforms Working across LLMs, RAG, embeddings and semantic search Supporting AI deployment, governance and integration patterns Collaborating with engineering, data, DevOps and business teams Advising clients on AI platform capability and implementation strategy Environment Python LLMs, prompt engineering, fine-tuning, RAG LangChain, LangGraph, Agent frameworks Vector databases and semantic search MLOps and LLMOps AWS, Azure, GCP, Databricks Containerisation, Kubernetes and GPU infrastructure Requirements Experience designing enterprise AI or ML architectures Strong understanding of cloud and modern data platforms Exposure to scalable AI deployment and integration patterns Financial Services or regulated industry experience essential Strong stakeholder engagement and communication skills Open to candidates from Manager through to Associate Director level.
19/07/2026
Full time
AI Solution Architects & Technical AI Leaders Manchester Hybrid We're supporting a major consulting and technology organisation delivering enterprise AI and data transformation programmes across Financial Services. The focus is designing scalable AI architectures that move beyond proof of concept into secure, production-grade deployment across banking environments. Hiring across multiple levels, from Solution Architects through to senior technical leadership. What you'll be doing Designing AI and GenAI architecture strategies and roadmaps Building scalable AI/ML and Agentic AI platforms Working across LLMs, RAG, embeddings and semantic search Supporting AI deployment, governance and integration patterns Collaborating with engineering, data, DevOps and business teams Advising clients on AI platform capability and implementation strategy Environment Python LLMs, prompt engineering, fine-tuning, RAG LangChain, LangGraph, Agent frameworks Vector databases and semantic search MLOps and LLMOps AWS, Azure, GCP, Databricks Containerisation, Kubernetes and GPU infrastructure Requirements Experience designing enterprise AI or ML architectures Strong understanding of cloud and modern data platforms Exposure to scalable AI deployment and integration patterns Financial Services or regulated industry experience essential Strong stakeholder engagement and communication skills Open to candidates from Manager through to Associate Director level.
