As a Senior Data Engineer at CGI, you will design, build, and optimise data platforms that underpin critical national services in the healthcare sector. Responsibilities You'll use AWS, Databricks, and Python to deliver high-impact solutions that improve outcomes, enhance decision-making, and drive innovation across the sector. You'll collaborate with experts who share a passion for problem-solving, ownership, and technical excellence. Qualifications Must hold UK Security Clearance or be eligible to go through this clearance. Benefits Competitive salary, excellent pension, private healthcare, and a share scheme (3.5% + 3.5% matching) which makes you a CGI Partner. Hybrid position based in Leeds.
27/06/2026
Full time
As a Senior Data Engineer at CGI, you will design, build, and optimise data platforms that underpin critical national services in the healthcare sector. Responsibilities You'll use AWS, Databricks, and Python to deliver high-impact solutions that improve outcomes, enhance decision-making, and drive innovation across the sector. You'll collaborate with experts who share a passion for problem-solving, ownership, and technical excellence. Qualifications Must hold UK Security Clearance or be eligible to go through this clearance. Benefits Competitive salary, excellent pension, private healthcare, and a share scheme (3.5% + 3.5% matching) which makes you a CGI Partner. Hybrid position based in Leeds.
Introduction 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. Our rapid expansion has been powered by consistently strong growth across diverse sales channels, the smooth integration of retailer acquisitions, and impressive customer retention. We continue to lead and redefine the energy market through innovative time of use tariffs and data driven commercial strategies that transform how customers engage with energy. We empower customers with dynamic pricing and Intelligent EV charging, rewarding them for shifting consumption to greener, cheaper periods. Role Summary You will lead the GB Commercial Analytics "pod", owning pricing operations, commercial reporting, and growth insight to drive sales, margin, compliance, and customer satisfaction. You will act as a strategic business partner to Commercial, Sales, Marketing and Energy Markets teams, combining hands on technical expertise with strong team leadership. What you'll do Set priorities and guide work & output of a small, high-performance data team. 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. Partner with Commercial, Sales, Marketing, Energy Markets, Flexibility, Gross Margin and Strategic Finance teams to provide forecasting inputs, KPI reporting, margin analysis and strategic support. Contribute to and collaborate with our global working groups to ensure and enable aligned reporting and shared analytics projects. Champion data best practices, integrity and continuous improvement in analytics engineering, tools and processes. What you'll have Proven experience mentoring and developing data professionals. Strong commercial acumen, preferably in pricing, margin optimisation, and/or growth analytics. Hands on expertise with modern data platforms and analytical tools. Strong communication skills to influence non-technical stakeholders and senior leadership. A track record of delivering actionable insights that drive measurable business impact. Our Data Platform Stack 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 Kubernetes for application deployment CI/CD with GitHub and CircleCI Infrastructure on AWS, deployed with Terraform / Spacelift Equal Opportunity Employer As an equal opportunity employer, we do not discriminate on the basis of any protected attribute. Our commitment is to provide equal opportunities, an inclusive work environment, and fairness for everyone.
26/06/2026
Full time
Introduction 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. Our rapid expansion has been powered by consistently strong growth across diverse sales channels, the smooth integration of retailer acquisitions, and impressive customer retention. We continue to lead and redefine the energy market through innovative time of use tariffs and data driven commercial strategies that transform how customers engage with energy. We empower customers with dynamic pricing and Intelligent EV charging, rewarding them for shifting consumption to greener, cheaper periods. Role Summary You will lead the GB Commercial Analytics "pod", owning pricing operations, commercial reporting, and growth insight to drive sales, margin, compliance, and customer satisfaction. You will act as a strategic business partner to Commercial, Sales, Marketing and Energy Markets teams, combining hands on technical expertise with strong team leadership. What you'll do Set priorities and guide work & output of a small, high-performance data team. 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. Partner with Commercial, Sales, Marketing, Energy Markets, Flexibility, Gross Margin and Strategic Finance teams to provide forecasting inputs, KPI reporting, margin analysis and strategic support. Contribute to and collaborate with our global working groups to ensure and enable aligned reporting and shared analytics projects. Champion data best practices, integrity and continuous improvement in analytics engineering, tools and processes. What you'll have Proven experience mentoring and developing data professionals. Strong commercial acumen, preferably in pricing, margin optimisation, and/or growth analytics. Hands on expertise with modern data platforms and analytical tools. Strong communication skills to influence non-technical stakeholders and senior leadership. A track record of delivering actionable insights that drive measurable business impact. Our Data Platform Stack 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 Kubernetes for application deployment CI/CD with GitHub and CircleCI Infrastructure on AWS, deployed with Terraform / Spacelift Equal Opportunity Employer As an equal opportunity employer, we do not discriminate on the basis of any protected attribute. Our commitment is to provide equal opportunities, an inclusive work environment, and fairness for everyone.
Join us to shape the future of AI/ML data platforms, where your expertise will help create resilient and market leading solutions. You will have the opportunity to collaborate with innovators across our global network, driving strategic change and mentoring others. We value your skills in solving complex challenges and fostering a culture of reliability and growth. At JPMorganChase, your impact will reach far beyond your team, opening doors to career advancement and meaningful relationships. As a Site Reliability Engineer in the AI/ML Data Platforms team, you will play a key role in building scalable and resilient data solutions. You will engage in root cause analysis, production changes, and operational improvements, while supporting budgetary and staffing decisions. You will mentor team members and partner with colleagues across the organization to drive strategic change. Your contributions will help shape a collaborative, innovative, and high performing team culture. Job Responsibilities Demonstrate expertise in application development and support across technologies such as Databricks, Snowflake, AWS, and Kubernetes Coordinate incident management coverage to ensure effective resolution of application issues Collaborate with cross functional teams to perform root cause analysis and implement production changes Develop and support AI/ML solutions for troubleshooting and incident resolution Mentor and guide team members to foster growth and drive strategic change Build and maintain scalable, resilient, and market leading data solutions Support budgetary and staffing considerations to optimize team performance Engage in operational stability and disaster recovery planning Implement automation tools to reduce toil and improve efficiency Ensure compliance with risk controls and company wide standards Build meaningful relationships across teams to achieve common goals Required Qualifications, Capabilities, and Skills Proficient in site reliability culture and principles, with experience implementing site reliability within applications or platforms Skilled in running production incident calls and managing incident resolution Experienced in observability, including white and black box monitoring, service level objective alerting, and telemetry collection using tools such as Grafana, Dynatrace, Prometheus, Datadog, and Splunk Strong understanding of SLI/SLO/SLA and Error Budgets Proficient in Python or PySpark for AI/ML modeling Able to reduce toil by building automation tools for repeated tasks Hands on experience in system design, resiliency, testing, operational stability, and disaster recovery Awareness of risk controls and compliance with departmental and company wide standards Collaborative team player with the ability to build meaningful relationships Preferred Qualifications, Capabilities, and Skills Experience in an SRE or production support role with AWS Cloud, Databricks, Snowflake, or similar technologies AWS and Databricks certifications Advanced knowledge of AI/ML troubleshooting and incident resolution Familiarity with budgetary and staffing optimization Experience mentoring and guiding team members Strong communication and interpersonal skills Demonstrated ability to drive strategic change across teams
26/06/2026
Full time
Join us to shape the future of AI/ML data platforms, where your expertise will help create resilient and market leading solutions. You will have the opportunity to collaborate with innovators across our global network, driving strategic change and mentoring others. We value your skills in solving complex challenges and fostering a culture of reliability and growth. At JPMorganChase, your impact will reach far beyond your team, opening doors to career advancement and meaningful relationships. As a Site Reliability Engineer in the AI/ML Data Platforms team, you will play a key role in building scalable and resilient data solutions. You will engage in root cause analysis, production changes, and operational improvements, while supporting budgetary and staffing decisions. You will mentor team members and partner with colleagues across the organization to drive strategic change. Your contributions will help shape a collaborative, innovative, and high performing team culture. Job Responsibilities Demonstrate expertise in application development and support across technologies such as Databricks, Snowflake, AWS, and Kubernetes Coordinate incident management coverage to ensure effective resolution of application issues Collaborate with cross functional teams to perform root cause analysis and implement production changes Develop and support AI/ML solutions for troubleshooting and incident resolution Mentor and guide team members to foster growth and drive strategic change Build and maintain scalable, resilient, and market leading data solutions Support budgetary and staffing considerations to optimize team performance Engage in operational stability and disaster recovery planning Implement automation tools to reduce toil and improve efficiency Ensure compliance with risk controls and company wide standards Build meaningful relationships across teams to achieve common goals Required Qualifications, Capabilities, and Skills Proficient in site reliability culture and principles, with experience implementing site reliability within applications or platforms Skilled in running production incident calls and managing incident resolution Experienced in observability, including white and black box monitoring, service level objective alerting, and telemetry collection using tools such as Grafana, Dynatrace, Prometheus, Datadog, and Splunk Strong understanding of SLI/SLO/SLA and Error Budgets Proficient in Python or PySpark for AI/ML modeling Able to reduce toil by building automation tools for repeated tasks Hands on experience in system design, resiliency, testing, operational stability, and disaster recovery Awareness of risk controls and compliance with departmental and company wide standards Collaborative team player with the ability to build meaningful relationships Preferred Qualifications, Capabilities, and Skills Experience in an SRE or production support role with AWS Cloud, Databricks, Snowflake, or similar technologies AWS and Databricks certifications Advanced knowledge of AI/ML troubleshooting and incident resolution Familiarity with budgetary and staffing optimization Experience mentoring and guiding team members Strong communication and interpersonal skills Demonstrated ability to drive strategic change across teams
Please note that this is a hybrid position in Cardiff with a mixture of in-office and home-based working. Every game is an ecosystem beyond mere gameplay. At Terminal Velocity, part of the Rocket Science Group, our platform and server teams are dedicated to constructing the infrastructure necessary for your game's global rollout through a strong focus on back-end and publishing stacks. We are looking for a Data Platform Engineer to help us design, build, and improve reliable data systems for our partners and internal teams. This is primarily a data engineering role. Your greatest strengths should be in areas such as data pipelines, data modelling, data quality, observability, and making data trustworthy. Adaptability is hugely important here. We work across a wide range of technical problems, so we are looking for someone who is also willing to step into adjacent areas such as backend services, web development, infrastructure, or SDK development when the opportunity arises. We do not expect you to be an expert in all of those areas. We care more about strong data engineering depth, good software engineering skills, curiosity, and the ability to learn quickly. About the Role: In this role, you will build scalable and resilient data solutions for games and related platforms. You may work on telemetry pipelines, analytics platforms, data warehouse and lakehouse design, reporting foundations, or backend integrations. You will be expected to speak directly with stakeholders and customers, clarify vague requirements, break down complex work, estimate and plan delivery, and make pragmatic technical trade-offs. Prior games industry experience is useful, but not required. Strong data engineering experience, good engineering judgement, and the ability to work with ambiguity are much more important. What We Value: Data Engineering: Strong experience designing, building, and operating reliable data platforms, pipelines, and data products. We are especially interested in people who understand data modelling, data quality, validation, observability, cost control, and how to make data trustworthy for technical and non-technical users. Technical Skills: We use a broad set of languages and technologies, and we are always happy to hear from candidates with experience in one or more of the following: Languages: Python, SQL, C#, Golang, Java, Kotlin, TypeScript, or Rust Data Platforms: BigQuery, Snowflake, Redshift, Databricks, PostgreSQL, MySQL, MongoDB, or other SQL/NoSQL technologies Data Tooling: Airflow, dbt, AWS Glue, Step Functions, Spark, Hadoop, or similar tooling Infrastructure: AWS, Terraform, Docker, Kubernetes, or other cloud/platform technologies CI/CD: GitHub Actions, Jenkins, ArgoCD, or similar deployment tooling Adaptability: This is primarily a data engineering role, but we value engineers who are willing to step into adjacent areas when needed. That might include backend services, infrastructure, web development, SDK development, telemetry integrations, tooling, or unfamiliar client systems. We do not expect expertise in all of these areas, but curiosity and willingness to learn are important. AI: A willingness to experiment with and embrace AI to help improve the efficiency and quality of our output. Problem-Solving: Strong analytical and problem-solving skills, with a proactive approach to identifying and addressing technical challenges, especially in messy or ambiguous data environments. Self-Motivation: Capacity for self-motivation, the ability to work independently, and the judgement to make sensible progress without every requirement being fully defined. Stakeholder Communication: The ability to speak directly with technical and non-technical stakeholders, ask good questions, explain trade-offs, and build shared understanding. Competitive Salary and Benefits Package: Your health and wellbeing is important to us, so we offer a variety of benefits including: Private Pension via Salary Sacrifice Optional Private Medical, Dental, and Vision Coverage Annual Leave, plus Bank Holidays and Winter Break Office Closure What We Can Offer Annual Research Credit: provides all members with an annual credit to further enhance your skills! Professional Development: offers annual reviews, opportunities to collaborate across disciplines, internal tech talks, and the chance to learn from specialists across games & software development industries. Work-Life Balance: we Believe home life comes first, flexible working environment, and we don't crunch. Family Friendly: offer 6 weeks full of Maternity, Paternity, and Adoption Leave to support our team. Office Perks: Weekly Team Lunches, Snacks (including good tea), Fully Equipped Team Lounge with favourite consoles & games, supportive & creative working environment. Benefits Package: Private Pension, Private Medical, Dental, Vision, Annual Leave, Bank Holidays. A Friendly Note from the Recruitment Team Let us do the work for you: Even if your profile isn't an exact match for all of the qualifications listed above, we still want you to apply. Our team members come from a variety of different industries, not all of which are immediately relevant to game or software development, and we welcome all candidates of similarly varied backgrounds, communities, and identities. Rocket Science is an equal opportunity employer and is committed to providing a worry-free workplace void of discrimination or harassment. Rocket Scientists are expected to foster and champion an environment in which everyone has the opportunity to feel included and is afforded the respect and dignity they deserve. Rocket Science does not accept unsolicited résumés from recruiters, employment agencies, or staffing firms.
26/06/2026
Full time
Please note that this is a hybrid position in Cardiff with a mixture of in-office and home-based working. Every game is an ecosystem beyond mere gameplay. At Terminal Velocity, part of the Rocket Science Group, our platform and server teams are dedicated to constructing the infrastructure necessary for your game's global rollout through a strong focus on back-end and publishing stacks. We are looking for a Data Platform Engineer to help us design, build, and improve reliable data systems for our partners and internal teams. This is primarily a data engineering role. Your greatest strengths should be in areas such as data pipelines, data modelling, data quality, observability, and making data trustworthy. Adaptability is hugely important here. We work across a wide range of technical problems, so we are looking for someone who is also willing to step into adjacent areas such as backend services, web development, infrastructure, or SDK development when the opportunity arises. We do not expect you to be an expert in all of those areas. We care more about strong data engineering depth, good software engineering skills, curiosity, and the ability to learn quickly. About the Role: In this role, you will build scalable and resilient data solutions for games and related platforms. You may work on telemetry pipelines, analytics platforms, data warehouse and lakehouse design, reporting foundations, or backend integrations. You will be expected to speak directly with stakeholders and customers, clarify vague requirements, break down complex work, estimate and plan delivery, and make pragmatic technical trade-offs. Prior games industry experience is useful, but not required. Strong data engineering experience, good engineering judgement, and the ability to work with ambiguity are much more important. What We Value: Data Engineering: Strong experience designing, building, and operating reliable data platforms, pipelines, and data products. We are especially interested in people who understand data modelling, data quality, validation, observability, cost control, and how to make data trustworthy for technical and non-technical users. Technical Skills: We use a broad set of languages and technologies, and we are always happy to hear from candidates with experience in one or more of the following: Languages: Python, SQL, C#, Golang, Java, Kotlin, TypeScript, or Rust Data Platforms: BigQuery, Snowflake, Redshift, Databricks, PostgreSQL, MySQL, MongoDB, or other SQL/NoSQL technologies Data Tooling: Airflow, dbt, AWS Glue, Step Functions, Spark, Hadoop, or similar tooling Infrastructure: AWS, Terraform, Docker, Kubernetes, or other cloud/platform technologies CI/CD: GitHub Actions, Jenkins, ArgoCD, or similar deployment tooling Adaptability: This is primarily a data engineering role, but we value engineers who are willing to step into adjacent areas when needed. That might include backend services, infrastructure, web development, SDK development, telemetry integrations, tooling, or unfamiliar client systems. We do not expect expertise in all of these areas, but curiosity and willingness to learn are important. AI: A willingness to experiment with and embrace AI to help improve the efficiency and quality of our output. Problem-Solving: Strong analytical and problem-solving skills, with a proactive approach to identifying and addressing technical challenges, especially in messy or ambiguous data environments. Self-Motivation: Capacity for self-motivation, the ability to work independently, and the judgement to make sensible progress without every requirement being fully defined. Stakeholder Communication: The ability to speak directly with technical and non-technical stakeholders, ask good questions, explain trade-offs, and build shared understanding. Competitive Salary and Benefits Package: Your health and wellbeing is important to us, so we offer a variety of benefits including: Private Pension via Salary Sacrifice Optional Private Medical, Dental, and Vision Coverage Annual Leave, plus Bank Holidays and Winter Break Office Closure What We Can Offer Annual Research Credit: provides all members with an annual credit to further enhance your skills! Professional Development: offers annual reviews, opportunities to collaborate across disciplines, internal tech talks, and the chance to learn from specialists across games & software development industries. Work-Life Balance: we Believe home life comes first, flexible working environment, and we don't crunch. Family Friendly: offer 6 weeks full of Maternity, Paternity, and Adoption Leave to support our team. Office Perks: Weekly Team Lunches, Snacks (including good tea), Fully Equipped Team Lounge with favourite consoles & games, supportive & creative working environment. Benefits Package: Private Pension, Private Medical, Dental, Vision, Annual Leave, Bank Holidays. A Friendly Note from the Recruitment Team Let us do the work for you: Even if your profile isn't an exact match for all of the qualifications listed above, we still want you to apply. Our team members come from a variety of different industries, not all of which are immediately relevant to game or software development, and we welcome all candidates of similarly varied backgrounds, communities, and identities. Rocket Science is an equal opportunity employer and is committed to providing a worry-free workplace void of discrimination or harassment. Rocket Scientists are expected to foster and champion an environment in which everyone has the opportunity to feel included and is afforded the respect and dignity they deserve. Rocket Science does not accept unsolicited résumés from recruiters, employment agencies, or staffing firms.
Blended Working We operate a blended working model, with colleagues spending at least two days per week in the office, aligned to project team requirements. Occasional travel to client sites may also be required. Thisbalancehelpsusstayconnected,learnfromeachother,andbuildstrongrelationships-bothwithinourteamandwiththebusinesseswesupport. The Role As a Senior Data Engineer at Oakland, you'll lead the delivery of high-quality data solutions for our clients. You'll take ownership of projects end-to-end - setting the technical direction, getting stuck into the build, and making sure what we deliver is solid, scalable, and genuinely useful. No two projects are the same, so you'll be working across different industries, technologies, and problem spaces. It's a mix of hands-on engineering and leadership - supporting others, making key decisions, and helping projects land well. Our work covers Data Strategy, Data Management, Data Platforms, AI, and Analytics. You'll be joining a consultancy that prides itself on shaping solutions that deliver business value and lasting impact, and you'll be working alongside a talented team of 25+ Engineers & Architects, sharing ideas, supporting each other, and helping raise the bar across the team. We're tech-agnostic and client-first - we use whatever works best, whether that's our own platform or tools from partners like Microsoft, AWS, Databricks, Snowflake, etc. What We're Looking For You're an experienced Data Engineer who's comfortable owning things from start to finish. You've delivered complex projects before and know what "good" looks like - from code quality to architecture, to working with stakeholders. You're still hands-on (this isn't a pure leadership role), but you're also happy leading workstreams, guiding others, and making calls when needed. At this level, we'd expect you to: Design and build robust, scalable data solutions Take the lead on projects or key pieces of work Set and maintain high engineering standards Support and mentor other Engineers Work directly with clients to understand problems and shape solutions You don't need to know every tool, but you should be adaptable and open to learning - we work across a pretty broad ecosystem of technologies. The Skillset We're looking for a mix not all! of the experience and skills below: Strong experience with Python and SQL Solid experience designing and building cloud-based data solutions (Azure preferred, AWS/GCP also fine) Experience building and maintaining complex data pipelines at scale Hands-on experience with modern platforms such as Fabric, Snowflake, or Databricks An understanding of data modelling, architecture, and how platforms fit together Experience with DevOps practices (CI/CD, testing, monitoring) Experience working from requirements through to delivery Comfortable working with clients and stakeholders Relevant certifications from Microsoft, AWS, Snowflake, and GCP are desirable, but not essential Benefits that put you first At Oakland, we believe in taking care of our people - both inside and outside of work. Here's what you can expect when you join us: Health & Wellbeing - Enjoy Private Healthcare from day one for you and your household, including dental cover, physiotherapy, mental health support, and access to a range of wellbeing services to keep you feeling your best. Discretionary Bonus - Your hard work won't go unnoticed. When we do well, you'll do well. Generous Pension - We invest in your future with a 10% employer contribution, plus flexible options so you can adjust to your investment preferences. Electric Vehicle Scheme - Drive greener with tax-efficient options to get behind the wheel of an electric car. Giving Back - Support causes you care about with our Payroll Giving Scheme and Matched Charitable Giving program. Bike to Work Scheme - Save money, stay active, and enjoy tax savings on a new bike. Family-Friendly Policies - We support all paths to parenthood with: Enhanced Maternity Pay - 16 weeks full pay, 10 weeks half pay. Enhanced Paternity Pay - 2 weeks full pay, 2 weeks half pay. Adoption, Surrogacy & Shared Parental Leave. Fertility Treatment Support - Because your family matters. Time to Recharge - 25 days annual leave + bank holidays (and your allowance grows the longer you're with us!). Learning & Development - We invest in you with: Personalised development plans tailored to your goals. Full support for certifications. Access to The Oakland Academy for a suite of learning materials. An annual Personal Learning Budget to upskill in ways that matter to you. Refer & Earn - Know someone great? If they join us, you'll get a referral bonus as a thank you. Diversity, Equity, Inclusion & Belonging at Oakland At Oakland, we believe that diverse perspectives drive better outcomes for our people, our clients, and our business. Our commitment to DEIB isn't just about policies; it's about creating a workplace where everyone feels heard, valued, and empowered to thrive. We are building a truly inclusive Oakland where you can be yourself, no matter your background, gender, age, race, ethnicity, disability, sexual orientation, or any other characteristic that makes you, you. Fair & Inclusive Hiring - Every interviewer completes recruitment and unconscious bias training, and our hiring process is skills-based and structured to ensure fairness and consistency for all candidates. Support Throughout the Interview Process - If you require any reasonable accommodations to make your interview experience more accessible, our Talent team is here to help. Just let us know.
26/06/2026
Full time
Blended Working We operate a blended working model, with colleagues spending at least two days per week in the office, aligned to project team requirements. Occasional travel to client sites may also be required. Thisbalancehelpsusstayconnected,learnfromeachother,andbuildstrongrelationships-bothwithinourteamandwiththebusinesseswesupport. The Role As a Senior Data Engineer at Oakland, you'll lead the delivery of high-quality data solutions for our clients. You'll take ownership of projects end-to-end - setting the technical direction, getting stuck into the build, and making sure what we deliver is solid, scalable, and genuinely useful. No two projects are the same, so you'll be working across different industries, technologies, and problem spaces. It's a mix of hands-on engineering and leadership - supporting others, making key decisions, and helping projects land well. Our work covers Data Strategy, Data Management, Data Platforms, AI, and Analytics. You'll be joining a consultancy that prides itself on shaping solutions that deliver business value and lasting impact, and you'll be working alongside a talented team of 25+ Engineers & Architects, sharing ideas, supporting each other, and helping raise the bar across the team. We're tech-agnostic and client-first - we use whatever works best, whether that's our own platform or tools from partners like Microsoft, AWS, Databricks, Snowflake, etc. What We're Looking For You're an experienced Data Engineer who's comfortable owning things from start to finish. You've delivered complex projects before and know what "good" looks like - from code quality to architecture, to working with stakeholders. You're still hands-on (this isn't a pure leadership role), but you're also happy leading workstreams, guiding others, and making calls when needed. At this level, we'd expect you to: Design and build robust, scalable data solutions Take the lead on projects or key pieces of work Set and maintain high engineering standards Support and mentor other Engineers Work directly with clients to understand problems and shape solutions You don't need to know every tool, but you should be adaptable and open to learning - we work across a pretty broad ecosystem of technologies. The Skillset We're looking for a mix not all! of the experience and skills below: Strong experience with Python and SQL Solid experience designing and building cloud-based data solutions (Azure preferred, AWS/GCP also fine) Experience building and maintaining complex data pipelines at scale Hands-on experience with modern platforms such as Fabric, Snowflake, or Databricks An understanding of data modelling, architecture, and how platforms fit together Experience with DevOps practices (CI/CD, testing, monitoring) Experience working from requirements through to delivery Comfortable working with clients and stakeholders Relevant certifications from Microsoft, AWS, Snowflake, and GCP are desirable, but not essential Benefits that put you first At Oakland, we believe in taking care of our people - both inside and outside of work. Here's what you can expect when you join us: Health & Wellbeing - Enjoy Private Healthcare from day one for you and your household, including dental cover, physiotherapy, mental health support, and access to a range of wellbeing services to keep you feeling your best. Discretionary Bonus - Your hard work won't go unnoticed. When we do well, you'll do well. Generous Pension - We invest in your future with a 10% employer contribution, plus flexible options so you can adjust to your investment preferences. Electric Vehicle Scheme - Drive greener with tax-efficient options to get behind the wheel of an electric car. Giving Back - Support causes you care about with our Payroll Giving Scheme and Matched Charitable Giving program. Bike to Work Scheme - Save money, stay active, and enjoy tax savings on a new bike. Family-Friendly Policies - We support all paths to parenthood with: Enhanced Maternity Pay - 16 weeks full pay, 10 weeks half pay. Enhanced Paternity Pay - 2 weeks full pay, 2 weeks half pay. Adoption, Surrogacy & Shared Parental Leave. Fertility Treatment Support - Because your family matters. Time to Recharge - 25 days annual leave + bank holidays (and your allowance grows the longer you're with us!). Learning & Development - We invest in you with: Personalised development plans tailored to your goals. Full support for certifications. Access to The Oakland Academy for a suite of learning materials. An annual Personal Learning Budget to upskill in ways that matter to you. Refer & Earn - Know someone great? If they join us, you'll get a referral bonus as a thank you. Diversity, Equity, Inclusion & Belonging at Oakland At Oakland, we believe that diverse perspectives drive better outcomes for our people, our clients, and our business. Our commitment to DEIB isn't just about policies; it's about creating a workplace where everyone feels heard, valued, and empowered to thrive. We are building a truly inclusive Oakland where you can be yourself, no matter your background, gender, age, race, ethnicity, disability, sexual orientation, or any other characteristic that makes you, you. Fair & Inclusive Hiring - Every interviewer completes recruitment and unconscious bias training, and our hiring process is skills-based and structured to ensure fairness and consistency for all candidates. Support Throughout the Interview Process - If you require any reasonable accommodations to make your interview experience more accessible, our Talent team is here to help. Just let us know.
Senior Data Engineer - Palantir Foundry As a Senior Data Engineer, you'll play a key role in building a modern, large scale data platform, designing reliable and scalable pipelines that support critical business outcomes. Working closely with data leaders and delivery teams, you'll shape engineering standards, improve data quality, and enable trusted insights. Drive measurable change by shaping and delivering large scale data products and platforms using Palantir Foundry and cloud native tooling. Engineer scalable pipelines, transform complex datasets into operational decision making assets. Partner with clients to unlock efficiency and insight across critical programmes. Build reusable patterns, improve observability and accelerate client roadmaps for modern data adoption. Location: Swansea, Wales - hybrid (on site presence two days per week). UK security clearance required. Senior Data Engineer - Healthcare In this role you'll design, build and optimise data platforms that underpin critical national services. The focus is on AWS, Databricks and Python to deliver high impact solutions that improve outcomes and drive innovation across the sector. Collaborate with Healthcare stakeholders to define requirements and translate them into data solutions. Build and maintain scalable data pipelines using AWS services and Apache Spark on Databricks. Ensure data quality, governance and security across the data ecosystem. Enable data driven decision making for national healthcare services. Location: Leeds, United Kingdom - hybrid. UK security clearance required. Senior Data Analyst / Analytics Engineer Design and deliver high quality dashboards using Power BI, Tableau, SQL, Excel and related technologies. Partner with business stakeholders to gather requirements and translate them into effective analytics solutions. Build and maintain robust data models, ensuring data quality, accuracy and adherence to governance standards. Drive reporting automation and continuous improvement of analytics frameworks. Present insights, trends and recommendations to senior leadership and cross functional teams. Champion best practices across data modelling, visualisation and reporting standards. 5+ years of experience in Data Analytics, Analytics Engineering, Business Intelligence or related disciplines. Advanced proficiency in Power BI and SQL. Extensive experience in data modelling, data transformation and dashboard development. Proven stakeholder management skills and ability to gather requirements effectively. Excellent communication and data storytelling skills. Desirable: Experience with Power Automate, Azure, Tableau or Python; Power BI and/or Azure certifications. Location: United Kingdom - hybrid.
26/06/2026
Full time
Senior Data Engineer - Palantir Foundry As a Senior Data Engineer, you'll play a key role in building a modern, large scale data platform, designing reliable and scalable pipelines that support critical business outcomes. Working closely with data leaders and delivery teams, you'll shape engineering standards, improve data quality, and enable trusted insights. Drive measurable change by shaping and delivering large scale data products and platforms using Palantir Foundry and cloud native tooling. Engineer scalable pipelines, transform complex datasets into operational decision making assets. Partner with clients to unlock efficiency and insight across critical programmes. Build reusable patterns, improve observability and accelerate client roadmaps for modern data adoption. Location: Swansea, Wales - hybrid (on site presence two days per week). UK security clearance required. Senior Data Engineer - Healthcare In this role you'll design, build and optimise data platforms that underpin critical national services. The focus is on AWS, Databricks and Python to deliver high impact solutions that improve outcomes and drive innovation across the sector. Collaborate with Healthcare stakeholders to define requirements and translate them into data solutions. Build and maintain scalable data pipelines using AWS services and Apache Spark on Databricks. Ensure data quality, governance and security across the data ecosystem. Enable data driven decision making for national healthcare services. Location: Leeds, United Kingdom - hybrid. UK security clearance required. Senior Data Analyst / Analytics Engineer Design and deliver high quality dashboards using Power BI, Tableau, SQL, Excel and related technologies. Partner with business stakeholders to gather requirements and translate them into effective analytics solutions. Build and maintain robust data models, ensuring data quality, accuracy and adherence to governance standards. Drive reporting automation and continuous improvement of analytics frameworks. Present insights, trends and recommendations to senior leadership and cross functional teams. Champion best practices across data modelling, visualisation and reporting standards. 5+ years of experience in Data Analytics, Analytics Engineering, Business Intelligence or related disciplines. Advanced proficiency in Power BI and SQL. Extensive experience in data modelling, data transformation and dashboard development. Proven stakeholder management skills and ability to gather requirements effectively. Excellent communication and data storytelling skills. Desirable: Experience with Power Automate, Azure, Tableau or Python; Power BI and/or Azure certifications. Location: United Kingdom - hybrid.
Senior Data Engineer - Palantir Foundry As a Senior Data Engineer, you'll play a key role in building a modern, large scale data platform, designing reliable and scalable pipelines that support critical business outcomes. Working closely with data leaders and delivery teams, you'll shape engineering standards, improve data quality, and enable trusted insights. Drive measurable change by shaping and delivering large scale data products and platforms using Palantir Foundry and cloud native tooling. Engineer scalable pipelines, transform complex datasets into operational decision making assets. Partner with clients to unlock efficiency and insight across critical programmes. Build reusable patterns, improve observability and accelerate client roadmaps for modern data adoption. Location: Swansea, Wales - hybrid (on site presence two days per week). UK security clearance required. Senior Data Engineer - Healthcare In this role you'll design, build and optimise data platforms that underpin critical national services. The focus is on AWS, Databricks and Python to deliver high impact solutions that improve outcomes and drive innovation across the sector. Collaborate with Healthcare stakeholders to define requirements and translate them into data solutions. Build and maintain scalable data pipelines using AWS services and Apache Spark on Databricks. Ensure data quality, governance and security across the data ecosystem. Enable data driven decision making for national healthcare services. Location: Leeds, United Kingdom - hybrid. UK security clearance required. Senior Data Analyst / Analytics Engineer Design and deliver high quality dashboards using Power BI, Tableau, SQL, Excel and related technologies. Partner with business stakeholders to gather requirements and translate them into effective analytics solutions. Build and maintain robust data models, ensuring data quality, accuracy and adherence to governance standards. Drive reporting automation and continuous improvement of analytics frameworks. Present insights, trends and recommendations to senior leadership and cross functional teams. Champion best practices across data modelling, visualisation and reporting standards. 5+ years of experience in Data Analytics, Analytics Engineering, Business Intelligence or related disciplines. Advanced proficiency in Power BI and SQL. Extensive experience in data modelling, data transformation and dashboard development. Proven stakeholder management skills and ability to gather requirements effectively. Excellent communication and data storytelling skills. Desirable: Experience with Power Automate, Azure, Tableau or Python; Power BI and/or Azure certifications. Location: United Kingdom - hybrid.
26/06/2026
Full time
Senior Data Engineer - Palantir Foundry As a Senior Data Engineer, you'll play a key role in building a modern, large scale data platform, designing reliable and scalable pipelines that support critical business outcomes. Working closely with data leaders and delivery teams, you'll shape engineering standards, improve data quality, and enable trusted insights. Drive measurable change by shaping and delivering large scale data products and platforms using Palantir Foundry and cloud native tooling. Engineer scalable pipelines, transform complex datasets into operational decision making assets. Partner with clients to unlock efficiency and insight across critical programmes. Build reusable patterns, improve observability and accelerate client roadmaps for modern data adoption. Location: Swansea, Wales - hybrid (on site presence two days per week). UK security clearance required. Senior Data Engineer - Healthcare In this role you'll design, build and optimise data platforms that underpin critical national services. The focus is on AWS, Databricks and Python to deliver high impact solutions that improve outcomes and drive innovation across the sector. Collaborate with Healthcare stakeholders to define requirements and translate them into data solutions. Build and maintain scalable data pipelines using AWS services and Apache Spark on Databricks. Ensure data quality, governance and security across the data ecosystem. Enable data driven decision making for national healthcare services. Location: Leeds, United Kingdom - hybrid. UK security clearance required. Senior Data Analyst / Analytics Engineer Design and deliver high quality dashboards using Power BI, Tableau, SQL, Excel and related technologies. Partner with business stakeholders to gather requirements and translate them into effective analytics solutions. Build and maintain robust data models, ensuring data quality, accuracy and adherence to governance standards. Drive reporting automation and continuous improvement of analytics frameworks. Present insights, trends and recommendations to senior leadership and cross functional teams. Champion best practices across data modelling, visualisation and reporting standards. 5+ years of experience in Data Analytics, Analytics Engineering, Business Intelligence or related disciplines. Advanced proficiency in Power BI and SQL. Extensive experience in data modelling, data transformation and dashboard development. Proven stakeholder management skills and ability to gather requirements effectively. Excellent communication and data storytelling skills. Desirable: Experience with Power Automate, Azure, Tableau or Python; Power BI and/or Azure certifications. Location: United Kingdom - hybrid.
Req ID: CSQ127R149 Location: London, United Kingdom - Hybrid Recruiter: Dina Hussain We're hiring for multiple roles within our FDE team. As a Forward Deployed Engineer (FDE), you will work with customers to build and productionize solutions to their data & AI challenges using the Databricks platform. You will own the architecture, lead design decisions, and implement end-to-end systems spanning data engineering, AI, and application development. We work cross-functionally to shape long-term strategic priorities and initiatives alongside engineering, product, and developer relations. FDEs deliver with customer empathy, integrating with client systems, training, and other technical needs to help customers get the most value out of their data. This is a hands on, customer facing role for builders who thrive at the intersection of technology and business impact. The ideal candidate combines engineering expertise with adaptability, curiosity, and a passion for working with customers and teammates to solve complex problems that drive measurable outcomes. FDEs are billable and know how to complete projects according to specifications with exceptional customer empathy. The impact you will have Production Solution Delivery: Lead impactful customer technical projects by delivering production grade systems, designing and building reference architectures, custom applications and data ingestion and ML/AI model integration Transformational Impact: Guide strategic customers as they implement transformational big data projects, including end to end design, build and deployment of industry leading big data and AI applications. Work with engagement managers to scope technical delivery work with input from the customer Empower Customers: Guide customers on architecture and design; bootstrap or implement customer projects that lead to a customer's successful understanding, evaluation and adoption of Databricks. Own the Architecture: Lead architecture and design decisions, ensuring solutions are secure, scalable, and aligned with both customer needs and Databricks best practices. Work with the Databricks technical team, Project Manager, Architect and Customer team to ensure the technical components of the engagement are delivered to meet customers' needs. Work with Engineering and Databricks Customer Support to provide product and implementation feedback and to guide rapid resolution for engagement specific product and support issues. Customer Immersion: Embed with customer teams, engaging with stakeholders from technical ICs to executives to deeply understand challenges and deliver impact. Reusable Assets & Scale: Contribute accelerators, frameworks, and best practices that scale impact across accounts and influence the Databricks product roadmap. What we look for Experience in data engineering, data platforms & analytics, or software engineering / full stack development Comfortable writing code in either Python, Scala, JavaScript/TypeScript, and modern frameworks Working knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one Deep experience with distributed computing with Apache Spark and knowledge of Spark runtime internals Familiarity with CI/CD for production deployments Working knowledge of MLOps, ML/AI models and AI APIs Design and deployment of performant production end to end data architectures and applications that combine data pipelines, ML/AI models, and user facing interfaces. Experience with technical project delivery - managing scope, timelines and measurable outcomes, translating complex concepts into actionable solutions. Documentation and white boarding skills. Experience working with enterprise clients and managing conflicts across a broad stakeholder range Build skills in technical areas, and demonstrate curiosity, adaptability, and eagerness to explore new technologies which support the deployment and integration of Databricks based solutions to complete customer projects. Travel to customers 20% of the time Databricks Certification - an advantage About Databricks Databricks is the data and AI company. More than 10,000 organizations worldwide - including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 - rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark , Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook. Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here. Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio economic status, veteran status, and other protected characteristics. Compliance If access to export controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.
26/06/2026
Full time
Req ID: CSQ127R149 Location: London, United Kingdom - Hybrid Recruiter: Dina Hussain We're hiring for multiple roles within our FDE team. As a Forward Deployed Engineer (FDE), you will work with customers to build and productionize solutions to their data & AI challenges using the Databricks platform. You will own the architecture, lead design decisions, and implement end-to-end systems spanning data engineering, AI, and application development. We work cross-functionally to shape long-term strategic priorities and initiatives alongside engineering, product, and developer relations. FDEs deliver with customer empathy, integrating with client systems, training, and other technical needs to help customers get the most value out of their data. This is a hands on, customer facing role for builders who thrive at the intersection of technology and business impact. The ideal candidate combines engineering expertise with adaptability, curiosity, and a passion for working with customers and teammates to solve complex problems that drive measurable outcomes. FDEs are billable and know how to complete projects according to specifications with exceptional customer empathy. The impact you will have Production Solution Delivery: Lead impactful customer technical projects by delivering production grade systems, designing and building reference architectures, custom applications and data ingestion and ML/AI model integration Transformational Impact: Guide strategic customers as they implement transformational big data projects, including end to end design, build and deployment of industry leading big data and AI applications. Work with engagement managers to scope technical delivery work with input from the customer Empower Customers: Guide customers on architecture and design; bootstrap or implement customer projects that lead to a customer's successful understanding, evaluation and adoption of Databricks. Own the Architecture: Lead architecture and design decisions, ensuring solutions are secure, scalable, and aligned with both customer needs and Databricks best practices. Work with the Databricks technical team, Project Manager, Architect and Customer team to ensure the technical components of the engagement are delivered to meet customers' needs. Work with Engineering and Databricks Customer Support to provide product and implementation feedback and to guide rapid resolution for engagement specific product and support issues. Customer Immersion: Embed with customer teams, engaging with stakeholders from technical ICs to executives to deeply understand challenges and deliver impact. Reusable Assets & Scale: Contribute accelerators, frameworks, and best practices that scale impact across accounts and influence the Databricks product roadmap. What we look for Experience in data engineering, data platforms & analytics, or software engineering / full stack development Comfortable writing code in either Python, Scala, JavaScript/TypeScript, and modern frameworks Working knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one Deep experience with distributed computing with Apache Spark and knowledge of Spark runtime internals Familiarity with CI/CD for production deployments Working knowledge of MLOps, ML/AI models and AI APIs Design and deployment of performant production end to end data architectures and applications that combine data pipelines, ML/AI models, and user facing interfaces. Experience with technical project delivery - managing scope, timelines and measurable outcomes, translating complex concepts into actionable solutions. Documentation and white boarding skills. Experience working with enterprise clients and managing conflicts across a broad stakeholder range Build skills in technical areas, and demonstrate curiosity, adaptability, and eagerness to explore new technologies which support the deployment and integration of Databricks based solutions to complete customer projects. Travel to customers 20% of the time Databricks Certification - an advantage About Databricks Databricks is the data and AI company. More than 10,000 organizations worldwide - including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 - rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark , Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook. Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here. Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio economic status, veteran status, and other protected characteristics. Compliance If access to export controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.
Senior Forward Deployed Engineer (FDE, Full Stack) London, United Kingdom (Hybrid) Recruiter: Dina Hussain We're hiring for multiple roles within our FDE team. As a Forward Deployed Engineer (FDE), you will work with customers to build and productionize solutions to their data & AI challenges using the Databricks platform. You will own the architecture, lead design decisions, and implement end to end systems spanning data engineering, AI, and application development. We work cross functionally to shape long term strategic priorities and initiatives alongside engineering, product, and developer relations. FDEs deliver with customer empathy, integrating with client systems, training, and other technical needs to help customers get the most value out of their data. This is a hands on, customer facing role for builders who thrive at the intersection of technology and business impact. The ideal candidate combines engineering expertise with adaptability, curiosity, and a passion for working with customers and teammates to solve complex problems that drive measurable outcomes. FDEs are billable and know how to complete projects according to specifications with exceptional customer empathy. Impact you will have Production Solution Delivery: Lead impactful customer technical projects by delivering production grade systems, designing and building reference architectures, custom applications and data ingestion and ML/AI model integration Transformational Impact: Guide strategic customers as they implement transformational big data projects, including end to end design, build and deployment of industry leading big data and AI applications. Work with engagement managers to scope technical delivery work with input from the customer Empower Customers: Guide customers on architecture and design; bootstrap or implement customer projects that lead to a customer's successful understanding, evaluation and adoption of Databricks. Own the Architecture: Lead architecture and design decisions, ensuring solutions are secure, scalable, and aligned with both customer needs and Databricks best practices. Work with the Databricks technical team, Project Manager, Architect and Customer team to ensure the technical components of the engagement are delivered to meet customers' needs. Work with Engineering and Databricks Customer Support to provide product and implementation feedback and to guide rapid resolution for engagement specific product and support issues. Customer Immersion: Embed with customer teams, engaging with stakeholders from technical ICs to executives to deeply understand challenges and deliver impact. Reusable Assets & Scale: Contribute accelerators, frameworks, and best practices that scale impact across accounts and influence the Databricks product roadmap. What we look for Experience in data engineering, data platforms & analytics, or software engineering / full stack development Working knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one Deep experience with distributed computing with Apache Spark and knowledge of Spark runtime internals Familiarity with CI/CD for production deployments Working knowledge of MLOps, ML/AI models and AI APIs Design and deployment of performant production end to end data architectures and applications that combine data pipelines, ML/AI models, and user facing interfaces. Experience with technical project delivery - managing scope, timelines and measurable outcomes, translating complex concepts into actionable solutions. Documentation and white boarding skills. Experience working with enterprise clients and managing conflicts across a broad stakeholder range. Build skills in technical areas, and demonstrate curiosity, adaptability, and eagerness to explore new technologies which support the deployment and integration of Databricks based solutions to complete customer projects. Travel to customers 20% of the time. Databricks Certification - an advantage. Benefits Databricks offers comprehensive benefits and perks that meet the needs of all of its employees. Specific details on the benefits offered in your region are available upon request. Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio economic status, veteran status, and other protected characteristics. Compliance If access to export controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.
26/06/2026
Full time
Senior Forward Deployed Engineer (FDE, Full Stack) London, United Kingdom (Hybrid) Recruiter: Dina Hussain We're hiring for multiple roles within our FDE team. As a Forward Deployed Engineer (FDE), you will work with customers to build and productionize solutions to their data & AI challenges using the Databricks platform. You will own the architecture, lead design decisions, and implement end to end systems spanning data engineering, AI, and application development. We work cross functionally to shape long term strategic priorities and initiatives alongside engineering, product, and developer relations. FDEs deliver with customer empathy, integrating with client systems, training, and other technical needs to help customers get the most value out of their data. This is a hands on, customer facing role for builders who thrive at the intersection of technology and business impact. The ideal candidate combines engineering expertise with adaptability, curiosity, and a passion for working with customers and teammates to solve complex problems that drive measurable outcomes. FDEs are billable and know how to complete projects according to specifications with exceptional customer empathy. Impact you will have Production Solution Delivery: Lead impactful customer technical projects by delivering production grade systems, designing and building reference architectures, custom applications and data ingestion and ML/AI model integration Transformational Impact: Guide strategic customers as they implement transformational big data projects, including end to end design, build and deployment of industry leading big data and AI applications. Work with engagement managers to scope technical delivery work with input from the customer Empower Customers: Guide customers on architecture and design; bootstrap or implement customer projects that lead to a customer's successful understanding, evaluation and adoption of Databricks. Own the Architecture: Lead architecture and design decisions, ensuring solutions are secure, scalable, and aligned with both customer needs and Databricks best practices. Work with the Databricks technical team, Project Manager, Architect and Customer team to ensure the technical components of the engagement are delivered to meet customers' needs. Work with Engineering and Databricks Customer Support to provide product and implementation feedback and to guide rapid resolution for engagement specific product and support issues. Customer Immersion: Embed with customer teams, engaging with stakeholders from technical ICs to executives to deeply understand challenges and deliver impact. Reusable Assets & Scale: Contribute accelerators, frameworks, and best practices that scale impact across accounts and influence the Databricks product roadmap. What we look for Experience in data engineering, data platforms & analytics, or software engineering / full stack development Working knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one Deep experience with distributed computing with Apache Spark and knowledge of Spark runtime internals Familiarity with CI/CD for production deployments Working knowledge of MLOps, ML/AI models and AI APIs Design and deployment of performant production end to end data architectures and applications that combine data pipelines, ML/AI models, and user facing interfaces. Experience with technical project delivery - managing scope, timelines and measurable outcomes, translating complex concepts into actionable solutions. Documentation and white boarding skills. Experience working with enterprise clients and managing conflicts across a broad stakeholder range. Build skills in technical areas, and demonstrate curiosity, adaptability, and eagerness to explore new technologies which support the deployment and integration of Databricks based solutions to complete customer projects. Travel to customers 20% of the time. Databricks Certification - an advantage. Benefits Databricks offers comprehensive benefits and perks that meet the needs of all of its employees. Specific details on the benefits offered in your region are available upon request. Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio economic status, veteran status, and other protected characteristics. Compliance If access to export controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.
JOB DESCRIPTION Become a member of a team where you can contribute significantly to shaping the future of a world-renowned and influential company. Among top performers, you can make a direct and meaningful impact. As a Lead Engineer at JPMorgan Chase within our Market Data Services team you will play a pivotal role in designing, delivering and maintaining critical data distribution systems within the firm. These systems encompass both on premises and cloud based infrastructure to deliver third party data to multiple lines of business. You will be working within an Agile project environment collaborating closely with cross functional teams to deliver high quality solutions to our clients. Job Responsibilities Applies deep technical expertise and problem solving methodologies focused on analyzing complex data and systems, anticipating issues, considering upstream and downstream implications, and advising on mitigation actions. Uses enterprise authorized AI capabilities within the work environment to accelerate analysis of complex infrastructure signals and documentation of mitigation options, validating outputs and handling operational data according to sensitivity and security requirements. Designing and maintaining critical data delivery systems - encompassing both realtime data, historical data and AI/ML use cases. Collaboration with product owners and stakeholders to ensure data solutions align with business and regulatory requirements. Capable of finding a balance between best of breed and cost effective solutions. Act as a positive team player who is capable of accepting different intellectual points of view. Clear and concise communicator; ability to present to senior management. Ability to analyze and articulate problems and provide input into solutions. Provide 3rd level support to operational roles. A respect for strong process and control management disciplines. Leads reuse first adoption of AI assisted practices across delivery and automation routines to reduce recurring issues, ensuring changes are validated, traceable and auditable, and aligned to resiliency and security expectations. Required qualifications, capabilities, and skills Formal training or certification on infrastructure engineering concepts and advanced applied experience in cloud technologies including Kubernetes, Terraform and AWS. Data Lake technologies (e.g. Snowflake, Databricks, AWS Glue/Athena, Lake Formation). Demonstrated experience using enterprise authorized AI capabilities within the work environment to support infrastructure engineering workflows with strong validation habits and awareness of data sensitivity. Ability to review and validate AI assisted recommendations before implementation, escalating when uncertain and ensuring outcomes align to resiliency, security and auditability expectations. Network architecture and protocols. Programming languages (e.g. Java, Python, C++). Market Data / messaging products (e.g. TREP, Vela, RedLine, Bloomberg BPIPE, Solace, AMPS, etc.). Market Data vendors and their key products (e.g. Bloomberg, LSEG, Factset, S&P). Database technologies and SQL scripting. Monitoring tools (ITRS Geneos, Dynatrace, Datadog). ABOUT US J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world's most prominent corporations, governments, wealthy individuals and institutional investors. Our first class business in a first class way approach to serving clients drives everything we do. We strive to build trusted, long term partnerships to help our clients achieve their business objectives. We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. ABOUT THE TEAM J.P. Morgan's Commercial & Investment Bank is a global leader across banking, markets, securities services and payments. Corporations, governments and institutions throughout the world entrust us with their business in more than 100 countries. The Commercial & Investment Bank provides strategic advice, raises capital, manages risk and extends liquidity in markets around the world.
26/06/2026
Full time
JOB DESCRIPTION Become a member of a team where you can contribute significantly to shaping the future of a world-renowned and influential company. Among top performers, you can make a direct and meaningful impact. As a Lead Engineer at JPMorgan Chase within our Market Data Services team you will play a pivotal role in designing, delivering and maintaining critical data distribution systems within the firm. These systems encompass both on premises and cloud based infrastructure to deliver third party data to multiple lines of business. You will be working within an Agile project environment collaborating closely with cross functional teams to deliver high quality solutions to our clients. Job Responsibilities Applies deep technical expertise and problem solving methodologies focused on analyzing complex data and systems, anticipating issues, considering upstream and downstream implications, and advising on mitigation actions. Uses enterprise authorized AI capabilities within the work environment to accelerate analysis of complex infrastructure signals and documentation of mitigation options, validating outputs and handling operational data according to sensitivity and security requirements. Designing and maintaining critical data delivery systems - encompassing both realtime data, historical data and AI/ML use cases. Collaboration with product owners and stakeholders to ensure data solutions align with business and regulatory requirements. Capable of finding a balance between best of breed and cost effective solutions. Act as a positive team player who is capable of accepting different intellectual points of view. Clear and concise communicator; ability to present to senior management. Ability to analyze and articulate problems and provide input into solutions. Provide 3rd level support to operational roles. A respect for strong process and control management disciplines. Leads reuse first adoption of AI assisted practices across delivery and automation routines to reduce recurring issues, ensuring changes are validated, traceable and auditable, and aligned to resiliency and security expectations. Required qualifications, capabilities, and skills Formal training or certification on infrastructure engineering concepts and advanced applied experience in cloud technologies including Kubernetes, Terraform and AWS. Data Lake technologies (e.g. Snowflake, Databricks, AWS Glue/Athena, Lake Formation). Demonstrated experience using enterprise authorized AI capabilities within the work environment to support infrastructure engineering workflows with strong validation habits and awareness of data sensitivity. Ability to review and validate AI assisted recommendations before implementation, escalating when uncertain and ensuring outcomes align to resiliency, security and auditability expectations. Network architecture and protocols. Programming languages (e.g. Java, Python, C++). Market Data / messaging products (e.g. TREP, Vela, RedLine, Bloomberg BPIPE, Solace, AMPS, etc.). Market Data vendors and their key products (e.g. Bloomberg, LSEG, Factset, S&P). Database technologies and SQL scripting. Monitoring tools (ITRS Geneos, Dynatrace, Datadog). ABOUT US J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world's most prominent corporations, governments, wealthy individuals and institutional investors. Our first class business in a first class way approach to serving clients drives everything we do. We strive to build trusted, long term partnerships to help our clients achieve their business objectives. We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. ABOUT THE TEAM J.P. Morgan's Commercial & Investment Bank is a global leader across banking, markets, securities services and payments. Corporations, governments and institutions throughout the world entrust us with their business in more than 100 countries. The Commercial & Investment Bank provides strategic advice, raises capital, manages risk and extends liquidity in markets around the world.
Novatus is a Series B scale-up RegTech SaaS provider and boutique advisory practice, enabling financial services firms to solve complex challenges and redefine what's possible through expert-led technology and consulting. Across both our technology and consulting services, Novatus delivers practical solutions to some of the most complex regulatory, data and operational challenges in financial services. Our SaaS platform, En>ACT ( short for Ensuring Accurate, Complete and Timely reporting ), is a market-leading solution for regulatory transaction reporting and reconciliation, providing real-time, independent oversight of transaction reporting across all global regulatory regimes. En>ACT is the only real-time assurance solution that tests 100% of transactions and 100% of fields, replacing sample-based reviews and static PDF reports delivered months after the event with live, actionable insights. This helps firms remediate quickly, reduce risk, and meet regulatory obligations with confidence. Already trusted by more than 45 firms worldwide, the platform is scalable, proven, and designed for both business and technical users. Alongside our SaaS offering, our unique model delivers consulting services to solve complex challenges, combining deep expertise, ownership and delivery to create lasting change. Our expertise spans Strategy & Operations, Data & AI, Risk & Resilience, Compliance, Transaction Reporting, and ESG. We embed ourselves within client teams to deliver both insight and execution, taking ownership of outcomes and driving measurable impact. Since our launch in 2019, we have scaled rapidly, creating space for our people to grow the business. Backed by North American private equity investment, and partnerships with the London Stock Exchange Group and Snowflake's global data platform, we are shaping the future of financial services through innovation in both consulting and technology. Now a team of 120 globally, our growth plans do not stop here: we are looking for top-tier talent to join us on our journey and enable our next phase of success. Senior DevOps Engineer Novatus HQ - 2 London Wall Place, EC2Y 5AU Job Overview: As a Senior DevOps Engineer , you will scope and deliver complex infrastructure projects end-to-end, building and maintaining scalable, secure, and performant systems. You'll contribute to our technology direction and drive initiatives that align with our business objectives, with an emphasis on automation, delivery pace, reliability, and cost efficiency. This role requires a strong technical background and a proven track record of building and scaling systems in complex environments. You'll be joining as we have begun actively modernizing our infrastructure from traditional deployments to automation and cloud-native systems with AWS, Terraform, GitHub Actions, Databricks, Snowflake and Grafana. Key Responsibilities: Design and implement AWS cloud infrastructure, writing clean and maintainable Infrastructure as Code for repeatable, auditable deployments across environments. Drive reliability, scalability, security, observability and cost efficiency of AWS infrastructure. Provide mentorship to other DevOps engineers, sharing expertise and raising engineering quality across the team. Develop and maintain robust and effective CI/CD pipelines. Troubleshoot and resolve complex infrastructure issues, ensuring minimal impact on business operations. Explore and evaluate new technologies, tools, and patterns that improve platform reliability and delivery pace. Partner with Data Engineering to support platform infrastructure (AWS, Databricks, Snowflake). About You: Requirements: Strong hands-on AWS infrastructure experience, including IAM, VPCs, compute, containers, load balancing, storage, security, resilience, and cost optimization. Hands-on experience deploying and operating applications on Kubernetes in production, including Helm/manifests, ingress, configuration/secrets, observability, and troubleshooting live workloads. Proficient with Infrastructure as Code, especially Terraform, with experience building maintainable, reusable modules and environment patterns. Solid production networking knowledge: TCP/IP, DNS, TLS, BGP, routing, subnets, NAT, firewalls/security groups, VPN/private connectivity, load balancers, and practical troubleshooting. Experience operating cloud infrastructure in regulated environments (e.g. GDPR, ISO 27001, SOC 2). Experience designing observability, monitoring, logging, and alerting solutions for distributed systems. Strong software engineering ability beyond basic scripting. Ideally someone who has contributed to larger software projects or built maintainable platform/backend tooling in a language such as Python, Go, Java, TypeScript, or similar. Comfortable using modern AI-assisted engineering workflows, including agentic coding tools and LLM-based automation. Familiarity with concepts such as MCP servers, tool-calling, RAG/vector search, embeddings, and AI-assisted platform operations. Working knowledge of databases and data platforms, including SQL databases such as PostgreSQL/MySQL and exposure to NoSQL or distributed data stores. Track record of independently scoping and delivering complex infrastructure projects end-to-end. Experience mentoring engineers and sharing technical expertise across a team. Excellent communication and stakeholder management skills. Nice-to-haves: Relevant certifications (e.g., AWS Certified Solutions Architect, AWS Certified Security, or AWS Certified DevOps Engineer). Databricks and/or Snowflake infrastructure experience. Kafka operations or other event streaming platforms. Experience on infrastructure modernization or migration programs. FinTech, RegTech, or financial services background. Why Join Us? Work Across Disciplines: You won't be confined to a single track- you will develop a broader skillset across our capabilities and offerings. Solve Problems that Matter: Work on complex challenges, where your thinking, analysis, and execution have real impact. Flat, Visible, Collaborative: We keep the structure flat, so you can collaborate directly with senior leaders and experienced specialists. Your work is visible, your perspectives are valued, and you will see the impact of your contributions every day. A Place for Builders: This is a great place for people who enjoy driving results and taking ownership. If you are driven to add value and help grow our business, you will enjoy a rewarding experience that recognises your contributions. Perks & Benefits: Private Medical Insurance (via AXA): includes mental health, dental, vision, and private GP access Life Insurance - 4 salary (via Unum) Unum's : includes GP access, medical second opinions, physiotherapy, lifestyle coaching, savings and discounts, mental health support, bereavement counselling, and cancer support services for you, your partner, and your child(ren) Salary sacrifice childcare and nursery scheme (via YellowNest) Employee Assistance Programme Enhanced parental leave (maternity & paternity) Professional qualification sponsorship Accelerated career progression based on readiness and performance, not tenure or time spent in role Holiday entitlement increases with tenure Flexible hours with core collaboration time Paid volunteering leave Gym & fitness discounts Bi-annual socials Office snacks and drinks Interest-based working groups to collaborate and innovate Novatus' Equal Opportunities Statement: Novatus is an Equal Opportunity Employer. All employment decisions are made based on business needs, role requirements, and individual qualifications, without regard to race, age, religion or belief, sex, sexual orientation, gender identity or expression, marital or civil partnership status, pregnancy or maternity, socioeconomic background, disability, or any other characteristic protected under the Equality Act 2010. We maintain a workplace culture that is inclusive, respectful, and supportive. Our recruitment and selection processes are designed to ensure fairness and consistency for all candidates. Reasonable adjustments are available throughout the application and interview process, and candidates are encouraged to contact Human Resources to discuss any specific requirements. This commitment is embedded in all aspects of our employment practices, including recruitment, compensation, professional development, promotion, and workplace conduct.
26/06/2026
Full time
Novatus is a Series B scale-up RegTech SaaS provider and boutique advisory practice, enabling financial services firms to solve complex challenges and redefine what's possible through expert-led technology and consulting. Across both our technology and consulting services, Novatus delivers practical solutions to some of the most complex regulatory, data and operational challenges in financial services. Our SaaS platform, En>ACT ( short for Ensuring Accurate, Complete and Timely reporting ), is a market-leading solution for regulatory transaction reporting and reconciliation, providing real-time, independent oversight of transaction reporting across all global regulatory regimes. En>ACT is the only real-time assurance solution that tests 100% of transactions and 100% of fields, replacing sample-based reviews and static PDF reports delivered months after the event with live, actionable insights. This helps firms remediate quickly, reduce risk, and meet regulatory obligations with confidence. Already trusted by more than 45 firms worldwide, the platform is scalable, proven, and designed for both business and technical users. Alongside our SaaS offering, our unique model delivers consulting services to solve complex challenges, combining deep expertise, ownership and delivery to create lasting change. Our expertise spans Strategy & Operations, Data & AI, Risk & Resilience, Compliance, Transaction Reporting, and ESG. We embed ourselves within client teams to deliver both insight and execution, taking ownership of outcomes and driving measurable impact. Since our launch in 2019, we have scaled rapidly, creating space for our people to grow the business. Backed by North American private equity investment, and partnerships with the London Stock Exchange Group and Snowflake's global data platform, we are shaping the future of financial services through innovation in both consulting and technology. Now a team of 120 globally, our growth plans do not stop here: we are looking for top-tier talent to join us on our journey and enable our next phase of success. Senior DevOps Engineer Novatus HQ - 2 London Wall Place, EC2Y 5AU Job Overview: As a Senior DevOps Engineer , you will scope and deliver complex infrastructure projects end-to-end, building and maintaining scalable, secure, and performant systems. You'll contribute to our technology direction and drive initiatives that align with our business objectives, with an emphasis on automation, delivery pace, reliability, and cost efficiency. This role requires a strong technical background and a proven track record of building and scaling systems in complex environments. You'll be joining as we have begun actively modernizing our infrastructure from traditional deployments to automation and cloud-native systems with AWS, Terraform, GitHub Actions, Databricks, Snowflake and Grafana. Key Responsibilities: Design and implement AWS cloud infrastructure, writing clean and maintainable Infrastructure as Code for repeatable, auditable deployments across environments. Drive reliability, scalability, security, observability and cost efficiency of AWS infrastructure. Provide mentorship to other DevOps engineers, sharing expertise and raising engineering quality across the team. Develop and maintain robust and effective CI/CD pipelines. Troubleshoot and resolve complex infrastructure issues, ensuring minimal impact on business operations. Explore and evaluate new technologies, tools, and patterns that improve platform reliability and delivery pace. Partner with Data Engineering to support platform infrastructure (AWS, Databricks, Snowflake). About You: Requirements: Strong hands-on AWS infrastructure experience, including IAM, VPCs, compute, containers, load balancing, storage, security, resilience, and cost optimization. Hands-on experience deploying and operating applications on Kubernetes in production, including Helm/manifests, ingress, configuration/secrets, observability, and troubleshooting live workloads. Proficient with Infrastructure as Code, especially Terraform, with experience building maintainable, reusable modules and environment patterns. Solid production networking knowledge: TCP/IP, DNS, TLS, BGP, routing, subnets, NAT, firewalls/security groups, VPN/private connectivity, load balancers, and practical troubleshooting. Experience operating cloud infrastructure in regulated environments (e.g. GDPR, ISO 27001, SOC 2). Experience designing observability, monitoring, logging, and alerting solutions for distributed systems. Strong software engineering ability beyond basic scripting. Ideally someone who has contributed to larger software projects or built maintainable platform/backend tooling in a language such as Python, Go, Java, TypeScript, or similar. Comfortable using modern AI-assisted engineering workflows, including agentic coding tools and LLM-based automation. Familiarity with concepts such as MCP servers, tool-calling, RAG/vector search, embeddings, and AI-assisted platform operations. Working knowledge of databases and data platforms, including SQL databases such as PostgreSQL/MySQL and exposure to NoSQL or distributed data stores. Track record of independently scoping and delivering complex infrastructure projects end-to-end. Experience mentoring engineers and sharing technical expertise across a team. Excellent communication and stakeholder management skills. Nice-to-haves: Relevant certifications (e.g., AWS Certified Solutions Architect, AWS Certified Security, or AWS Certified DevOps Engineer). Databricks and/or Snowflake infrastructure experience. Kafka operations or other event streaming platforms. Experience on infrastructure modernization or migration programs. FinTech, RegTech, or financial services background. Why Join Us? Work Across Disciplines: You won't be confined to a single track- you will develop a broader skillset across our capabilities and offerings. Solve Problems that Matter: Work on complex challenges, where your thinking, analysis, and execution have real impact. Flat, Visible, Collaborative: We keep the structure flat, so you can collaborate directly with senior leaders and experienced specialists. Your work is visible, your perspectives are valued, and you will see the impact of your contributions every day. A Place for Builders: This is a great place for people who enjoy driving results and taking ownership. If you are driven to add value and help grow our business, you will enjoy a rewarding experience that recognises your contributions. Perks & Benefits: Private Medical Insurance (via AXA): includes mental health, dental, vision, and private GP access Life Insurance - 4 salary (via Unum) Unum's : includes GP access, medical second opinions, physiotherapy, lifestyle coaching, savings and discounts, mental health support, bereavement counselling, and cancer support services for you, your partner, and your child(ren) Salary sacrifice childcare and nursery scheme (via YellowNest) Employee Assistance Programme Enhanced parental leave (maternity & paternity) Professional qualification sponsorship Accelerated career progression based on readiness and performance, not tenure or time spent in role Holiday entitlement increases with tenure Flexible hours with core collaboration time Paid volunteering leave Gym & fitness discounts Bi-annual socials Office snacks and drinks Interest-based working groups to collaborate and innovate Novatus' Equal Opportunities Statement: Novatus is an Equal Opportunity Employer. All employment decisions are made based on business needs, role requirements, and individual qualifications, without regard to race, age, religion or belief, sex, sexual orientation, gender identity or expression, marital or civil partnership status, pregnancy or maternity, socioeconomic background, disability, or any other characteristic protected under the Equality Act 2010. We maintain a workplace culture that is inclusive, respectful, and supportive. Our recruitment and selection processes are designed to ensure fairness and consistency for all candidates. Reasonable adjustments are available throughout the application and interview process, and candidates are encouraged to contact Human Resources to discuss any specific requirements. This commitment is embedded in all aspects of our employment practices, including recruitment, compensation, professional development, promotion, and workplace conduct.
Senior AI Engineer Manager/Associate Director Capital Markets Location: Manchester Working pattern: Hybrid Salary: Compensation aligned to experience and seniority Ref: J13116 Senior AI Engineering professionals are required to support the design, build and delivery of advanced AI solutions within financial services and capital markets environments. This role would suit an experienced professional with a strong background in AI engineering and enterprise solution delivery within complex environments. You will play a key role in shaping AI strategy, leading teams and delivering enterprise AI solutions, helping organisations solve complex operational, technical and regulatory challenges through AI adoption at scale. You will work across multidisciplinary teams, collaborating with data scientists, architects, MLOps/LLMOps engineers, business stakeholders and senior leadership to design, deliver and scale AI products, agentic AI solutions and data driven applications. Key responsibilities: Building and deploying AI prototypes, products and production ready solutions Designing and implementing end to end AI solutions that integrate with enterprise systems Working with LLMs, prompt engineering, RAG patterns, embeddings and fine tuning Developing AI agents and agentic workflows using modern frameworks Working with vector databases, APIs and modern data platforms Supporting AI deployment, serving patterns, evaluation frameworks and integration design Using Python and SQL to build robust, scalable AI and data solutions Working with cloud platforms such as AWS, Azure, GCP or Databricks Supporting MLOps, LLMOps, CI/CD and software engineering best practice Collaborating with technical and non-technical stakeholders across complex programmes Helping identify technical, delivery, security, data privacy and regulatory risks Contributing to technical documentation, solution design and delivery planning Supporting AI implementation and scaling initiatives across complex environments Leading and developing teams, supporting capability growth through mentoring, coaching and creating a collaborative, high performing environment Experience Required: Strong Python and SQL experience Applied AI engineering, ML engineering or software engineering background Experience with LLMs, RAG, embeddings, prompt engineering or fine tuning Exposure to LangChain, LangGraph, Agent Development Kit or similar agent frameworks Experience with vector databases such as Pinecone, Chroma or similar API development experience, ideally with FastAPI or similar frameworks Knowledge of MLOps, LLMOps, CI/CD or production deployment practices Experience designing or supporting evaluation frameworks for AI or agentic systems Experience working with modern data architectures and cloud platforms Understanding of AI risk, governance, security and regulatory considerations Financial services experience within capital markets or broader banking environments This is a strong opportunity for an AI engineering professional who wants to work on high impact AI and data transformation programmes within complex financial services environments.
26/06/2026
Full time
Senior AI Engineer Manager/Associate Director Capital Markets Location: Manchester Working pattern: Hybrid Salary: Compensation aligned to experience and seniority Ref: J13116 Senior AI Engineering professionals are required to support the design, build and delivery of advanced AI solutions within financial services and capital markets environments. This role would suit an experienced professional with a strong background in AI engineering and enterprise solution delivery within complex environments. You will play a key role in shaping AI strategy, leading teams and delivering enterprise AI solutions, helping organisations solve complex operational, technical and regulatory challenges through AI adoption at scale. You will work across multidisciplinary teams, collaborating with data scientists, architects, MLOps/LLMOps engineers, business stakeholders and senior leadership to design, deliver and scale AI products, agentic AI solutions and data driven applications. Key responsibilities: Building and deploying AI prototypes, products and production ready solutions Designing and implementing end to end AI solutions that integrate with enterprise systems Working with LLMs, prompt engineering, RAG patterns, embeddings and fine tuning Developing AI agents and agentic workflows using modern frameworks Working with vector databases, APIs and modern data platforms Supporting AI deployment, serving patterns, evaluation frameworks and integration design Using Python and SQL to build robust, scalable AI and data solutions Working with cloud platforms such as AWS, Azure, GCP or Databricks Supporting MLOps, LLMOps, CI/CD and software engineering best practice Collaborating with technical and non-technical stakeholders across complex programmes Helping identify technical, delivery, security, data privacy and regulatory risks Contributing to technical documentation, solution design and delivery planning Supporting AI implementation and scaling initiatives across complex environments Leading and developing teams, supporting capability growth through mentoring, coaching and creating a collaborative, high performing environment Experience Required: Strong Python and SQL experience Applied AI engineering, ML engineering or software engineering background Experience with LLMs, RAG, embeddings, prompt engineering or fine tuning Exposure to LangChain, LangGraph, Agent Development Kit or similar agent frameworks Experience with vector databases such as Pinecone, Chroma or similar API development experience, ideally with FastAPI or similar frameworks Knowledge of MLOps, LLMOps, CI/CD or production deployment practices Experience designing or supporting evaluation frameworks for AI or agentic systems Experience working with modern data architectures and cloud platforms Understanding of AI risk, governance, security and regulatory considerations Financial services experience within capital markets or broader banking environments This is a strong opportunity for an AI engineering professional who wants to work on high impact AI and data transformation programmes within complex financial services environments.
About Marex Marex Group plc (NASDAQ: MRX) is a diversified global financial services platform providing essential liquidity, market access and infrastructure services to clients across energy, commodities and financial markets. The group provides comprehensive breadth and depth of coverage across four core services: clearing, agency and execution, market making, and hedging and investment solutions. It has a leading franchise in many major metals, energy and agricultural products, with access to 60 exchanges. The group provides access to the world's major commodity markets, covering a broad range of clients that include some of the largest commodity producers, consumers and traders, banks, hedge funds and asset managers. With more than 40 offices worldwide, the group has over 3,000 employees across Europe, Asia and the Americas. For more information visit Position Reference: VN2644 Department description Marex has unique access across markets with significant share globally both on and off exchange. The depth of knowledge amongst its teams and divisions provides its customers with clear advantage, and its technology led service provides access to all major exchanges, order flow management via screen, voice and DMA, plus award winning data, insights and analytics. The Technology Department delivers secure, scalable digital tools, software services, and infrastructure across all business units. Agile development teams align with specific business areas, while other teams handle enterprise wide IT operations, support, security, and architecture. The Data & AI team drives productivity, compliance, and insights by leveraging a robust Data Lakehouse, decentralizing data access, improving client experiences, promoting data driven practices, and ensuring efficient, auditable use of data in line with commercial terms. Role Summary We are seeking a Principle DataOps Architect to own and embed a DataOps way of working across the enterprise data organisation. This is a greenfield role with a clear organisational mandate and significant scope to define how DataOps frameworks, tooling, and engineering standards are applied across our data platforms. The role is accountable for enabling the safe, reliable, and frequent delivery of production grade data capabilities, supporting real time management information, critical systems integration, advanced analytical and ML model refreshes, and accurate, timely data for customer facing AI solutions. Acting as a force multiplier for Data Engineering, AI/ML Engineering, and Analytics teams, the role combines deep technical leadership with senior level stakeholder engagement, shaping a culture of quality, automation, and operational excellence while translating governance, risk, and control requirements into engineering patterns that scale effectively and support delivery at the pace of the business. Responsibilities Design, implement, and operationalise the DataOps target state through consistent frameworks, tooling, and standards aligned with enterprise architecture, governance, and assurance requirements. Build and maintain CI/CD pipelines for data and ML workloads, enabling controlled, automated promotion across development, staging, and production environments. Enforce separation of duties between engineering and production administration to support regulatory, risk, and operational assurance requirements. Define and implement test driven development practices for data pipelines, including unit, integration, and end to end testing. Embed data reliability patterns aligned to the Medallion Architecture (Bronze, Silver, Gold). Implement data quality enforcement, monitoring, and observability frameworks to improve platform trust and stability. Apply software engineering and SDLC best practices consistently across data and ML workloads. Provide hands on technical leadership and design advisory services to Data Engineering, AI/ML Engineering, and Analytics teams, ensuring solutions align with DataOps standards and patterns. Build and maintain reusable DataOps toolkits, templates, and reference architectures to accelerate adoption and consistency. Partner with Governance, Risk, and Control stakeholders to translate policy and regulatory requirements into pragmatic, repeatable engineering controls. Support production readiness, release governance, and post incident learning for data platforms, contributing to continuous improvement in scalability, resilience, and operational excellence. Champion DataOps, analytics, and engineering best practices across technical and business teams, promoting a culture of automation, quality, and disciplined delivery. Ensure compliance with the company's regulatory requirements under the FCA. Adhere to the operational risk framework for your role ensuring that all regulatory or company determined parameters are complied with. Role model for demonstrating highest level standards of integrity and conduct and reflecting Company Values. At all times comply with the FCA's Code of Conduct. Ensure that you are fully aware of and adhere to internal policies that relate to you, your role or any other activities for which you have any level of responsibility. Report any breaches of policy to Compliance and/ or your supervisor as required. Escalate risk events immediately. Provide input to risk management processes, as required. Competencies, Skills, Experience & Qualifications Competencies Excellent verbal and written communication skills. A collaborative team player, approachable, self-efficient and influences a positive work environment. Demonstrates curiosity. Resilient in a challenging, fast paced environment. Ability to take a high level of responsibility in a fast pace and high volume environment. Excels at building relationships, networking and influencing others. Strategic collaborator with insight and agility, able to anticipate future challenges, ensuring operational effectiveness. Skills and Experience - Essential Strong experience implementing DataOps or DevOps practices in complex data environments. Proven expertise designing and operating CI/CD pipelines for data and analytics workloads. Hands on experience with Databricks (AWS and/or Azure) in production environments. Strong proficiency in Python and SQL. Experience applying Infrastructure as Code (IaC) using tools such as Terraform. Deep understanding of data platform reliability, observability, and quality controls. Strong knowledge of software engineering best practices and SDLC. Ability to operate as both hands on engineer and strategic enabler. Experience working in a regulated environment and knowledge of the risk and compliance requirements associated with this. Desirable Experience in financial services, with exposure to ETD and OTC derivative markets highly desirable. Hands on experience with Orchestration Platforms such as Azure Data Factory and Apache Airflow. Databricks Asset Bundles. Power BI. Data Transformation Platforms such as dbt and Databricks Lakeflow. Experience with Azure DevOps (ADO), Bitbucket, and Git based workflows. Advanced use of VS Code and developer productivity tooling (e.g. GitHub CoPilot). Experience supporting ML pipelines and model lifecycle operations. Prior involvement in building or scaling enterprise data platforms. Databricks Certified Data Engineer Professional. DAMA Certified Data Management Professional (CDMP). Conduct Rules Act with integrity Act with due skill, care and diligence Be open and cooperative with the FCA, the PRA and other regulators Pay due regard to the interests of customers and treat them fairly Observe proper standard of market conduct Act to deliver good outcomes for retail customers Company Values Respect - Clients are at the heart of our business, with superior execution and superb client service the foundation of the firm. We respect our clients and always treat them fairly. Integrity - Doing business the right way is the only way. We hold ourselves to a high ethical standard in everything we do - our clients expect this and we demand it of ourselves. Collaborative - We work in teams - open and direct communication and the willingness to work hard and collaboratively are the basis for effective teamwork. Working well with others is necessary for us to succeed at what we do. Developing our People - Our people are the basis of our competitive advantage. We look to "grow our own" and make Marex the place ambitious, hardworking, talented people choose to build their careers. Adaptable and Nimble - Our size and flexibility is an advantage. We are big enough to support our client's various needs, and adaptable and nimble enough to respond quickly to changing conditions or requirements. A non bureaucratic, but well controlled environment fosters initiative as well as employee satisfaction. Marex is fully committed to being an inclusive employer and providing an inclusive and accessible recruitment process for all. We will provide reasonable adjustments to remove any disadvantage to you being considered for this role. We value the differences that a diverse workforce brings to the company. We welcome applications from candidates returning to the workforce. Also . click apply for full job details
26/06/2026
Full time
About Marex Marex Group plc (NASDAQ: MRX) is a diversified global financial services platform providing essential liquidity, market access and infrastructure services to clients across energy, commodities and financial markets. The group provides comprehensive breadth and depth of coverage across four core services: clearing, agency and execution, market making, and hedging and investment solutions. It has a leading franchise in many major metals, energy and agricultural products, with access to 60 exchanges. The group provides access to the world's major commodity markets, covering a broad range of clients that include some of the largest commodity producers, consumers and traders, banks, hedge funds and asset managers. With more than 40 offices worldwide, the group has over 3,000 employees across Europe, Asia and the Americas. For more information visit Position Reference: VN2644 Department description Marex has unique access across markets with significant share globally both on and off exchange. The depth of knowledge amongst its teams and divisions provides its customers with clear advantage, and its technology led service provides access to all major exchanges, order flow management via screen, voice and DMA, plus award winning data, insights and analytics. The Technology Department delivers secure, scalable digital tools, software services, and infrastructure across all business units. Agile development teams align with specific business areas, while other teams handle enterprise wide IT operations, support, security, and architecture. The Data & AI team drives productivity, compliance, and insights by leveraging a robust Data Lakehouse, decentralizing data access, improving client experiences, promoting data driven practices, and ensuring efficient, auditable use of data in line with commercial terms. Role Summary We are seeking a Principle DataOps Architect to own and embed a DataOps way of working across the enterprise data organisation. This is a greenfield role with a clear organisational mandate and significant scope to define how DataOps frameworks, tooling, and engineering standards are applied across our data platforms. The role is accountable for enabling the safe, reliable, and frequent delivery of production grade data capabilities, supporting real time management information, critical systems integration, advanced analytical and ML model refreshes, and accurate, timely data for customer facing AI solutions. Acting as a force multiplier for Data Engineering, AI/ML Engineering, and Analytics teams, the role combines deep technical leadership with senior level stakeholder engagement, shaping a culture of quality, automation, and operational excellence while translating governance, risk, and control requirements into engineering patterns that scale effectively and support delivery at the pace of the business. Responsibilities Design, implement, and operationalise the DataOps target state through consistent frameworks, tooling, and standards aligned with enterprise architecture, governance, and assurance requirements. Build and maintain CI/CD pipelines for data and ML workloads, enabling controlled, automated promotion across development, staging, and production environments. Enforce separation of duties between engineering and production administration to support regulatory, risk, and operational assurance requirements. Define and implement test driven development practices for data pipelines, including unit, integration, and end to end testing. Embed data reliability patterns aligned to the Medallion Architecture (Bronze, Silver, Gold). Implement data quality enforcement, monitoring, and observability frameworks to improve platform trust and stability. Apply software engineering and SDLC best practices consistently across data and ML workloads. Provide hands on technical leadership and design advisory services to Data Engineering, AI/ML Engineering, and Analytics teams, ensuring solutions align with DataOps standards and patterns. Build and maintain reusable DataOps toolkits, templates, and reference architectures to accelerate adoption and consistency. Partner with Governance, Risk, and Control stakeholders to translate policy and regulatory requirements into pragmatic, repeatable engineering controls. Support production readiness, release governance, and post incident learning for data platforms, contributing to continuous improvement in scalability, resilience, and operational excellence. Champion DataOps, analytics, and engineering best practices across technical and business teams, promoting a culture of automation, quality, and disciplined delivery. Ensure compliance with the company's regulatory requirements under the FCA. Adhere to the operational risk framework for your role ensuring that all regulatory or company determined parameters are complied with. Role model for demonstrating highest level standards of integrity and conduct and reflecting Company Values. At all times comply with the FCA's Code of Conduct. Ensure that you are fully aware of and adhere to internal policies that relate to you, your role or any other activities for which you have any level of responsibility. Report any breaches of policy to Compliance and/ or your supervisor as required. Escalate risk events immediately. Provide input to risk management processes, as required. Competencies, Skills, Experience & Qualifications Competencies Excellent verbal and written communication skills. A collaborative team player, approachable, self-efficient and influences a positive work environment. Demonstrates curiosity. Resilient in a challenging, fast paced environment. Ability to take a high level of responsibility in a fast pace and high volume environment. Excels at building relationships, networking and influencing others. Strategic collaborator with insight and agility, able to anticipate future challenges, ensuring operational effectiveness. Skills and Experience - Essential Strong experience implementing DataOps or DevOps practices in complex data environments. Proven expertise designing and operating CI/CD pipelines for data and analytics workloads. Hands on experience with Databricks (AWS and/or Azure) in production environments. Strong proficiency in Python and SQL. Experience applying Infrastructure as Code (IaC) using tools such as Terraform. Deep understanding of data platform reliability, observability, and quality controls. Strong knowledge of software engineering best practices and SDLC. Ability to operate as both hands on engineer and strategic enabler. Experience working in a regulated environment and knowledge of the risk and compliance requirements associated with this. Desirable Experience in financial services, with exposure to ETD and OTC derivative markets highly desirable. Hands on experience with Orchestration Platforms such as Azure Data Factory and Apache Airflow. Databricks Asset Bundles. Power BI. Data Transformation Platforms such as dbt and Databricks Lakeflow. Experience with Azure DevOps (ADO), Bitbucket, and Git based workflows. Advanced use of VS Code and developer productivity tooling (e.g. GitHub CoPilot). Experience supporting ML pipelines and model lifecycle operations. Prior involvement in building or scaling enterprise data platforms. Databricks Certified Data Engineer Professional. DAMA Certified Data Management Professional (CDMP). Conduct Rules Act with integrity Act with due skill, care and diligence Be open and cooperative with the FCA, the PRA and other regulators Pay due regard to the interests of customers and treat them fairly Observe proper standard of market conduct Act to deliver good outcomes for retail customers Company Values Respect - Clients are at the heart of our business, with superior execution and superb client service the foundation of the firm. We respect our clients and always treat them fairly. Integrity - Doing business the right way is the only way. We hold ourselves to a high ethical standard in everything we do - our clients expect this and we demand it of ourselves. Collaborative - We work in teams - open and direct communication and the willingness to work hard and collaboratively are the basis for effective teamwork. Working well with others is necessary for us to succeed at what we do. Developing our People - Our people are the basis of our competitive advantage. We look to "grow our own" and make Marex the place ambitious, hardworking, talented people choose to build their careers. Adaptable and Nimble - Our size and flexibility is an advantage. We are big enough to support our client's various needs, and adaptable and nimble enough to respond quickly to changing conditions or requirements. A non bureaucratic, but well controlled environment fosters initiative as well as employee satisfaction. Marex is fully committed to being an inclusive employer and providing an inclusive and accessible recruitment process for all. We will provide reasonable adjustments to remove any disadvantage to you being considered for this role. We value the differences that a diverse workforce brings to the company. We welcome applications from candidates returning to the workforce. Also . click apply for full job details
Out of the successful launch of Chase in 2021, we're a new team, with a new mission. We're creating products that solve real world problems and put customers at the center - all in an environment that nurtures skills and helps you realize your potential. Our team is key to our success. We're people-first. We value collaboration, curiosity and commitment. As a Principal Software Engineer - Engineering Manager at JPMorganChase within the Accelerator Business, you would be responsible for the vision for the Data and AI capabilities of the platform - to enable product teams to focus on their core problems and platform would cover the rest. To give a not complete list of examples: data ingestion, transformation, exposing in various query engines, LLM patterns, audit, safety guardrails, compliance and observability. While we're looking for professional skills, culture is just as important to us. We understand that everyone's unique - and that diversity of thought, experience and background is what makes a good team, great. By bringing people with different points of view together, we can represent everyone and truly reflect the communities we serve. This way, there's scope for you to make a huge difference - on us as a company, and on our clients and business partners around the world. Technologies we use: Java, Kotlin, Kubernetes, Apache Kafka, GCP, BigQuery, Spark, VertexAI, ModelArmor, DeepEval, Google ADK. Job responsibilities: Set the vision and multi-year strategy for the Data & AI Platform that powers Chase's next-generation digital experiences, translating enterprise priorities into an executable roadmap and measurable outcomes. Lead and scale a multi-discipline organization spanning data platform engineering and AI/MLOps, establishing clear ownership, org structure, operating rhythms, and standards for delivery. Own the platform's end-to-end data foundation-ingestion, transformation, orchestration, metadata/catalog, quality, and governed data products-built for reliability, scalability, and self-service adoption. Serve as the executive steward for compliant use of customer data, ensuring privacy, access controls, lineage, retention, and auditability are embedded by design and aligned to firm risk and regulatory expectations. Define and deliver platform enablement for LLM-powered applications, including reference architectures, developer tooling, model onboarding and deployment patterns, evaluation and testing, observability, and cost/latency guardrails. Establish engineering excellence and operational maturity through SLOs, resiliency practices, incident management, release governance, capacity planning, and continuous improvement across the platform. Drive a product-oriented platform model by partnering with product, security, legal, risk, architecture, and engineering leaders to prioritize the highest-leverage capabilities and accelerate adoption across teams. Enable data-driven product development at scale through trusted analytics pipelines, standardized telemetry, experimentation support, and consistent metrics to inform decisions and improve customer outcomes. Attract, develop, and retain top talent by building leadership depth, setting high standards, coaching managers and senior engineers, and fostering a culture of ownership, inclusion, and accountability. Required qualifications, capabilities and skills Being a problem solver: you can independently analyze a problem and come up with options on how to solve it. Flexibility regarding tools and languages: for example you have to be open to debug an permission issue one day in a python service and dig into some Java/Kotlin out-of-memory issue the other day (of course we take into account your expertise and you will have team members to help you out!). Knowledge of data structures. Experience with either Kubernetes or Docker. Experience with cloud technologies (AWS/Azure/GCP) and distributed systems, web technologies and event driven architectures. Experience in leading people. Preferred qualifications, capabilities and skills Experience with message brokers (Kafka, RabbitMQ, Pulsar etc.). Experience with Kafka Connect. Preferably experience in setting up data platforms, setting standards - not just pipelines. Preferably experience in a distributed data processing environment/framework (e.g. Spark or Flink). Familiarity with advanced AI/ML concepts and protocols, such as Retrieval-Augmented Generation (RAG), agentic system architectures, and Model Context Protocol (MCP) Experience with MLOps tools and platforms (e.g., MLflow, Amazon SageMaker, Google VertexAI, Databricks, BentoML, KServe, Kubeflow) Experience with a deploying to a GenAI platform a production system: Google VertexAI, OpenAI, AWS Bedrock, LangChain, etc.
26/06/2026
Full time
Out of the successful launch of Chase in 2021, we're a new team, with a new mission. We're creating products that solve real world problems and put customers at the center - all in an environment that nurtures skills and helps you realize your potential. Our team is key to our success. We're people-first. We value collaboration, curiosity and commitment. As a Principal Software Engineer - Engineering Manager at JPMorganChase within the Accelerator Business, you would be responsible for the vision for the Data and AI capabilities of the platform - to enable product teams to focus on their core problems and platform would cover the rest. To give a not complete list of examples: data ingestion, transformation, exposing in various query engines, LLM patterns, audit, safety guardrails, compliance and observability. While we're looking for professional skills, culture is just as important to us. We understand that everyone's unique - and that diversity of thought, experience and background is what makes a good team, great. By bringing people with different points of view together, we can represent everyone and truly reflect the communities we serve. This way, there's scope for you to make a huge difference - on us as a company, and on our clients and business partners around the world. Technologies we use: Java, Kotlin, Kubernetes, Apache Kafka, GCP, BigQuery, Spark, VertexAI, ModelArmor, DeepEval, Google ADK. Job responsibilities: Set the vision and multi-year strategy for the Data & AI Platform that powers Chase's next-generation digital experiences, translating enterprise priorities into an executable roadmap and measurable outcomes. Lead and scale a multi-discipline organization spanning data platform engineering and AI/MLOps, establishing clear ownership, org structure, operating rhythms, and standards for delivery. Own the platform's end-to-end data foundation-ingestion, transformation, orchestration, metadata/catalog, quality, and governed data products-built for reliability, scalability, and self-service adoption. Serve as the executive steward for compliant use of customer data, ensuring privacy, access controls, lineage, retention, and auditability are embedded by design and aligned to firm risk and regulatory expectations. Define and deliver platform enablement for LLM-powered applications, including reference architectures, developer tooling, model onboarding and deployment patterns, evaluation and testing, observability, and cost/latency guardrails. Establish engineering excellence and operational maturity through SLOs, resiliency practices, incident management, release governance, capacity planning, and continuous improvement across the platform. Drive a product-oriented platform model by partnering with product, security, legal, risk, architecture, and engineering leaders to prioritize the highest-leverage capabilities and accelerate adoption across teams. Enable data-driven product development at scale through trusted analytics pipelines, standardized telemetry, experimentation support, and consistent metrics to inform decisions and improve customer outcomes. Attract, develop, and retain top talent by building leadership depth, setting high standards, coaching managers and senior engineers, and fostering a culture of ownership, inclusion, and accountability. Required qualifications, capabilities and skills Being a problem solver: you can independently analyze a problem and come up with options on how to solve it. Flexibility regarding tools and languages: for example you have to be open to debug an permission issue one day in a python service and dig into some Java/Kotlin out-of-memory issue the other day (of course we take into account your expertise and you will have team members to help you out!). Knowledge of data structures. Experience with either Kubernetes or Docker. Experience with cloud technologies (AWS/Azure/GCP) and distributed systems, web technologies and event driven architectures. Experience in leading people. Preferred qualifications, capabilities and skills Experience with message brokers (Kafka, RabbitMQ, Pulsar etc.). Experience with Kafka Connect. Preferably experience in setting up data platforms, setting standards - not just pipelines. Preferably experience in a distributed data processing environment/framework (e.g. Spark or Flink). Familiarity with advanced AI/ML concepts and protocols, such as Retrieval-Augmented Generation (RAG), agentic system architectures, and Model Context Protocol (MCP) Experience with MLOps tools and platforms (e.g., MLflow, Amazon SageMaker, Google VertexAI, Databricks, BentoML, KServe, Kubeflow) Experience with a deploying to a GenAI platform a production system: Google VertexAI, OpenAI, AWS Bedrock, LangChain, etc.
Hiring on behalf of a multi-strategy, multi-manager hedge fund is looking for a Data Architecture Lead to join their team. The firm trades globally across multiple asset classes and investment approaches. The primary focus of this role will be on the buildout and operations of a next generation security master system. In addition to designing and implementing robust data architectures. The successful candidate will lead the security master development team, overseeing the quality, performance, and scalability of the teams' deliverables. Key Responsibilities - Data Architecture and Design: Lead the design and implementation of the enterprise data architecture, ensuring alignment with the overall business strategy and objectives. Develop and maintain the data architecture for the security master system (secmaster), including data models, metadata, and data flow diagrams. Team Leadership: Lead and manage the secmaster team of python/sql engineers, providing guidance, mentorship, and support to team members. Establish and maintain data governance practices to ensure data quality, consistency, and security. Define data management policies and procedures, including data lineage, data cataloguing, and data retention. Monitor and optimize data processes to ensure efficient data integration, transformation, and storage. Technology Leadership: Evaluate and recommend data management tools and technologies to enhance the data architecture. Qualifications - Minimum of 7-10 years of experience in data architecture, data modelling, and data management, preferably within the financial services industry. Deep experience with security master systems (secmaster) in a hedge fund or investment management context. Deep knowledge of financial instruments in a variety of asset classes: equities, options, futures, credit products, etc. Technical Skills: Strong experience with the SQL Server platform and T-SQL querying. Familiarity with cloud data platforms (e.g., AWS, Azure) and big data technologies (e.g., Kafka, Spark, Databricks, Snowflake). Expert-level knowledge of building ETL processes in Python. Expert-level knowledge of performance tuning and optimization in a Python / SQL Server environment This role offers highly competitive compensation as well as a flexible hybrid working model.
26/06/2026
Full time
Hiring on behalf of a multi-strategy, multi-manager hedge fund is looking for a Data Architecture Lead to join their team. The firm trades globally across multiple asset classes and investment approaches. The primary focus of this role will be on the buildout and operations of a next generation security master system. In addition to designing and implementing robust data architectures. The successful candidate will lead the security master development team, overseeing the quality, performance, and scalability of the teams' deliverables. Key Responsibilities - Data Architecture and Design: Lead the design and implementation of the enterprise data architecture, ensuring alignment with the overall business strategy and objectives. Develop and maintain the data architecture for the security master system (secmaster), including data models, metadata, and data flow diagrams. Team Leadership: Lead and manage the secmaster team of python/sql engineers, providing guidance, mentorship, and support to team members. Establish and maintain data governance practices to ensure data quality, consistency, and security. Define data management policies and procedures, including data lineage, data cataloguing, and data retention. Monitor and optimize data processes to ensure efficient data integration, transformation, and storage. Technology Leadership: Evaluate and recommend data management tools and technologies to enhance the data architecture. Qualifications - Minimum of 7-10 years of experience in data architecture, data modelling, and data management, preferably within the financial services industry. Deep experience with security master systems (secmaster) in a hedge fund or investment management context. Deep knowledge of financial instruments in a variety of asset classes: equities, options, futures, credit products, etc. Technical Skills: Strong experience with the SQL Server platform and T-SQL querying. Familiarity with cloud data platforms (e.g., AWS, Azure) and big data technologies (e.g., Kafka, Spark, Databricks, Snowflake). Expert-level knowledge of building ETL processes in Python. Expert-level knowledge of performance tuning and optimization in a Python / SQL Server environment This role offers highly competitive compensation as well as a flexible hybrid working model.
Hiring on behalf of a multi-strategy, multi-manager hedge fund is looking for a Data Architecture Lead to join their team. The firm trades globally across multiple asset classes and investment approaches. The primary focus of this role will be on the buildout and operations of a next generation security master system. In addition to designing and implementing robust data architectures. The successful candidate will lead the security master development team, overseeing the quality, performance, and scalability of the teams' deliverables. Key Responsibilities - Data Architecture and Design: Lead the design and implementation of the enterprise data architecture, ensuring alignment with the overall business strategy and objectives. Develop and maintain the data architecture for the security master system (secmaster), including data models, metadata, and data flow diagrams. Team Leadership: Lead and manage the secmaster team of python/sql engineers, providing guidance, mentorship, and support to team members. Establish and maintain data governance practices to ensure data quality, consistency, and security. Define data management policies and procedures, including data lineage, data cataloguing, and data retention. Monitor and optimize data processes to ensure efficient data integration, transformation, and storage. Technology Leadership: Evaluate and recommend data management tools and technologies to enhance the data architecture. Qualifications - Minimum of 7-10 years of experience in data architecture, data modelling, and data management, preferably within the financial services industry. Deep experience with security master systems (secmaster) in a hedge fund or investment management context. Deep knowledge of financial instruments in a variety of asset classes: equities, options, futures, credit products, etc. Technical Skills: Strong experience with the SQL Server platform and T-SQL querying. Familiarity with cloud data platforms (e.g., AWS, Azure) and big data technologies (e.g., Kafka, Spark, Databricks, Snowflake). Expert-level knowledge of building ETL processes in Python. Expert-level knowledge of performance tuning and optimization in a Python / SQL Server environment This role offers highly competitive compensation as well as a flexible hybrid working model.
26/06/2026
Full time
Hiring on behalf of a multi-strategy, multi-manager hedge fund is looking for a Data Architecture Lead to join their team. The firm trades globally across multiple asset classes and investment approaches. The primary focus of this role will be on the buildout and operations of a next generation security master system. In addition to designing and implementing robust data architectures. The successful candidate will lead the security master development team, overseeing the quality, performance, and scalability of the teams' deliverables. Key Responsibilities - Data Architecture and Design: Lead the design and implementation of the enterprise data architecture, ensuring alignment with the overall business strategy and objectives. Develop and maintain the data architecture for the security master system (secmaster), including data models, metadata, and data flow diagrams. Team Leadership: Lead and manage the secmaster team of python/sql engineers, providing guidance, mentorship, and support to team members. Establish and maintain data governance practices to ensure data quality, consistency, and security. Define data management policies and procedures, including data lineage, data cataloguing, and data retention. Monitor and optimize data processes to ensure efficient data integration, transformation, and storage. Technology Leadership: Evaluate and recommend data management tools and technologies to enhance the data architecture. Qualifications - Minimum of 7-10 years of experience in data architecture, data modelling, and data management, preferably within the financial services industry. Deep experience with security master systems (secmaster) in a hedge fund or investment management context. Deep knowledge of financial instruments in a variety of asset classes: equities, options, futures, credit products, etc. Technical Skills: Strong experience with the SQL Server platform and T-SQL querying. Familiarity with cloud data platforms (e.g., AWS, Azure) and big data technologies (e.g., Kafka, Spark, Databricks, Snowflake). Expert-level knowledge of building ETL processes in Python. Expert-level knowledge of performance tuning and optimization in a Python / SQL Server environment This role offers highly competitive compensation as well as a flexible hybrid working model.
Senior Data Engineer Job Type: Full-time Salary Range: 45k - 60k Location: Hybrid working model with office days in Guildford or Lewes Join a leading public sector organisation as a Senior Data Engineer. This role offers the opportunity to significantly impact by leading the modernisation of data systems and ensuring community safety through high-quality data. Day-to-Day Responsibilities: Lead the modernisation of our client's data warehouse and implement Lakehouse architectures. Design, build, and optimise a secure, scalable cloud data platform within the Microsoft Fabric ecosystem. Architect and optimise high-performance, scalable data pipelines using SQL, Python, and Fabric Data Factory. Collaborate with business stakeholders, architects, analysts, and data scientists to deliver impactful data products. Serve as a technical leader-mentoring junior data engineers, driving best practices, and enhancing platform performance. Conduct monitoring, troubleshooting, root cause analysis, and performance optimisation of legacy data issues. Required Skills & Qualifications: Strong experience in delivering cloud data solutions, preferably in Microsoft Fabric or Azure. Experience with other platforms like AWS, Snowflake, or Databricks is also beneficial. Hands-on expertise with Data Factory (Fabric or Azure), notebooks (Python, PySpark), advanced SQL, and robust data modelling and performance optimisation skills. Proven track record in building scalable data pipelines and implementing modern architectures such as Medallion. Familiarity with CI/CD, Git, Azure DevOps, and API-based integrations. Excellent stakeholder engagement skills with the ability to translate business needs into technical solutions. Leadership capabilities with a proactive, solution-focused mindset. Nice to have: Experience with legacy technologies such as Oracle, SQL Server, SSIS, SAP Data Services, T-SQL, or PL/SQL. Benefits: Flexible working policies including job shares and part-time options. Agile working environment allowing management of your own diary and potential home working. Career progression opportunities. Contributory pension scheme. Generous annual leave allowance. Discounts for everyday spend, on-site gyms, and a range of sports clubs. Generous and supportive parental leave. Financial and mental wellbeing guidance and support. Discounted contributory healthcare scheme. If you are passionate about using data to drive safety and efficiency, and enjoy solving complex challenges in a dynamic environment, apply to join us as a Senior Data Engineer. Your work will have a real-world impact, helping to keep communities safe and secure. NB - there is a security check for this role requiring applicants to have been resident in the UK for at least the last five years To apply for this Senior Data Engineer position, please submit your CV today
25/06/2026
Full time
Senior Data Engineer Job Type: Full-time Salary Range: 45k - 60k Location: Hybrid working model with office days in Guildford or Lewes Join a leading public sector organisation as a Senior Data Engineer. This role offers the opportunity to significantly impact by leading the modernisation of data systems and ensuring community safety through high-quality data. Day-to-Day Responsibilities: Lead the modernisation of our client's data warehouse and implement Lakehouse architectures. Design, build, and optimise a secure, scalable cloud data platform within the Microsoft Fabric ecosystem. Architect and optimise high-performance, scalable data pipelines using SQL, Python, and Fabric Data Factory. Collaborate with business stakeholders, architects, analysts, and data scientists to deliver impactful data products. Serve as a technical leader-mentoring junior data engineers, driving best practices, and enhancing platform performance. Conduct monitoring, troubleshooting, root cause analysis, and performance optimisation of legacy data issues. Required Skills & Qualifications: Strong experience in delivering cloud data solutions, preferably in Microsoft Fabric or Azure. Experience with other platforms like AWS, Snowflake, or Databricks is also beneficial. Hands-on expertise with Data Factory (Fabric or Azure), notebooks (Python, PySpark), advanced SQL, and robust data modelling and performance optimisation skills. Proven track record in building scalable data pipelines and implementing modern architectures such as Medallion. Familiarity with CI/CD, Git, Azure DevOps, and API-based integrations. Excellent stakeholder engagement skills with the ability to translate business needs into technical solutions. Leadership capabilities with a proactive, solution-focused mindset. Nice to have: Experience with legacy technologies such as Oracle, SQL Server, SSIS, SAP Data Services, T-SQL, or PL/SQL. Benefits: Flexible working policies including job shares and part-time options. Agile working environment allowing management of your own diary and potential home working. Career progression opportunities. Contributory pension scheme. Generous annual leave allowance. Discounts for everyday spend, on-site gyms, and a range of sports clubs. Generous and supportive parental leave. Financial and mental wellbeing guidance and support. Discounted contributory healthcare scheme. If you are passionate about using data to drive safety and efficiency, and enjoy solving complex challenges in a dynamic environment, apply to join us as a Senior Data Engineer. Your work will have a real-world impact, helping to keep communities safe and secure. NB - there is a security check for this role requiring applicants to have been resident in the UK for at least the last five years To apply for this Senior Data Engineer position, please submit your CV today
JPMorgan's Global Liquidity and Cash Management Technology team is seeking a highly motivated Java and ReactJs engineers to join our global, diverse technology organization. We focus on providing modern solutions to support the Corporate & Investment Bank's Payments business. Our critical systems enable clients to monitor and manage their liquidity in real-time through a modern interactive analytical dashboard. As a Software Engineer II - Real-Time Client Liquidity Dashboard Java, ReactJs in the Global Liquidity and Cash Management Technology team, you will join our dynamic team as a hands on developer. We are continuing to invest in a new real time intraday liquidity monitoring dashboard, used globally by wholesale clients of our Payments business. The platform enables clients to manage their liquidity position via a rich, graphical, reactive user interface. As the product continues to grow, we are seeking hands on developers to join our dynamic team. You will contribute features, enhancements and bug fixes - ensuring our codebase remains modern, well structured and robust. You will collaborate with colleagues to perform technical analysis of client requirements, participate in estimation, planning, code reviews, architecture design sessions and retrospectives. This role offers the opportunity to learn about liquidity from colleagues, stakeholders and extensive training resources. You will have the chance to grow your skills through our curated technical development programs and dedicated training days. This exciting role provides you with the opportunity to see the direct impact of your contributions on the liquidity business and receive client feedback from around the globe. While banking experience is not required, you must be a passionate and well rounded technologist, eager to continuously learn and enhance your skills. Job responsibilities Design and develop technical solutions for a client facing real time liquidity dashboard. Incorporate security requirements and reviewing code written by team members using software engineering best practices. Write secure, high-quality and performant code with automated unit, component and integration tests. Produce architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by code. Identify opportunities to eliminate recurring issues to improve overall operational stability of software applications and systems. Participate in communities of practice across the group to drive awareness, consistency and adoption of modern technologies. Collaborate effectively as part of a global team. Provide technical leadership to small engineering sub teams focused on the delivery of a small epic by transforming requirements into stories and a build plan. Support junior colleagues in their technical growth. Provide out of hours application support and coordinate of Production releases. Required qualifications, capabilities, and skills Experience in enterprise software development. Understanding of Java fundamentals and frameworks (Spring Boot), OO programming paradigms, multi-threading, messaging technologies and computer networks. Proficient in coding UI focused technologies - React and TypeScript. Experience in building high-performance, real-time Java applications/user interfaces/APIs. Hands on experience with event driven architecture and distributed messaging technologies (Kafka). Experience in maintaining and troubleshooting software running in a Linux environment, familiarity with the Linux operating system, system utilities, containers and cloud architectures and services. Experience with modern testing tools (JUnit, Mockito, Spring Test Framework). Strong interpersonal and communication skills, with experience working with globally distributed engineers and stakeholders. Understanding of the full software development lifecycle and agile approach. Preferred qualifications, capabilities, and skills Experience of front-end development and front-end technologies, like ReactJs. AWS public cloud and infrastructure as code (Terraform) experience. Experience with gRPC and Google Protocol Buffers. Experience using and designing schemas/data structures in resilient SQL and NoSQL databases (e.g. Aurora PostgreSQL and DynamoDB). Certified Kubernetes and public cloud knowledge (e.g. CKAD and AWS certifications). Experience of automated integration and user interface testing. Experience of analytical data platforms (e.g. Databricks).
25/06/2026
Full time
JPMorgan's Global Liquidity and Cash Management Technology team is seeking a highly motivated Java and ReactJs engineers to join our global, diverse technology organization. We focus on providing modern solutions to support the Corporate & Investment Bank's Payments business. Our critical systems enable clients to monitor and manage their liquidity in real-time through a modern interactive analytical dashboard. As a Software Engineer II - Real-Time Client Liquidity Dashboard Java, ReactJs in the Global Liquidity and Cash Management Technology team, you will join our dynamic team as a hands on developer. We are continuing to invest in a new real time intraday liquidity monitoring dashboard, used globally by wholesale clients of our Payments business. The platform enables clients to manage their liquidity position via a rich, graphical, reactive user interface. As the product continues to grow, we are seeking hands on developers to join our dynamic team. You will contribute features, enhancements and bug fixes - ensuring our codebase remains modern, well structured and robust. You will collaborate with colleagues to perform technical analysis of client requirements, participate in estimation, planning, code reviews, architecture design sessions and retrospectives. This role offers the opportunity to learn about liquidity from colleagues, stakeholders and extensive training resources. You will have the chance to grow your skills through our curated technical development programs and dedicated training days. This exciting role provides you with the opportunity to see the direct impact of your contributions on the liquidity business and receive client feedback from around the globe. While banking experience is not required, you must be a passionate and well rounded technologist, eager to continuously learn and enhance your skills. Job responsibilities Design and develop technical solutions for a client facing real time liquidity dashboard. Incorporate security requirements and reviewing code written by team members using software engineering best practices. Write secure, high-quality and performant code with automated unit, component and integration tests. Produce architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by code. Identify opportunities to eliminate recurring issues to improve overall operational stability of software applications and systems. Participate in communities of practice across the group to drive awareness, consistency and adoption of modern technologies. Collaborate effectively as part of a global team. Provide technical leadership to small engineering sub teams focused on the delivery of a small epic by transforming requirements into stories and a build plan. Support junior colleagues in their technical growth. Provide out of hours application support and coordinate of Production releases. Required qualifications, capabilities, and skills Experience in enterprise software development. Understanding of Java fundamentals and frameworks (Spring Boot), OO programming paradigms, multi-threading, messaging technologies and computer networks. Proficient in coding UI focused technologies - React and TypeScript. Experience in building high-performance, real-time Java applications/user interfaces/APIs. Hands on experience with event driven architecture and distributed messaging technologies (Kafka). Experience in maintaining and troubleshooting software running in a Linux environment, familiarity with the Linux operating system, system utilities, containers and cloud architectures and services. Experience with modern testing tools (JUnit, Mockito, Spring Test Framework). Strong interpersonal and communication skills, with experience working with globally distributed engineers and stakeholders. Understanding of the full software development lifecycle and agile approach. Preferred qualifications, capabilities, and skills Experience of front-end development and front-end technologies, like ReactJs. AWS public cloud and infrastructure as code (Terraform) experience. Experience with gRPC and Google Protocol Buffers. Experience using and designing schemas/data structures in resilient SQL and NoSQL databases (e.g. Aurora PostgreSQL and DynamoDB). Certified Kubernetes and public cloud knowledge (e.g. CKAD and AWS certifications). Experience of automated integration and user interface testing. Experience of analytical data platforms (e.g. Databricks).
GT was founded in 2019 by a former Apple, Nest, and Google executive. GT's mission is to connect the world's best talent with product careers offered by high-growth companies in the UK, USA, Canada, Germany, and the Netherlands. Our clients operate in industries like healthcare, life sciences, fintech, retail, e-commerce, finance and many more - giving our team exposure to real world, high impact projects. About the Role We're looking for a Senior Data Scientist / ML Engineer to join a UK based client in the healthcare and pharmacy domain. The role combines forecasting and machine learning with end to end ownership of solution delivery, from project discovery and stakeholder collaboration through model development, deployment, and productionisation. Location: Nottingham, UK Office attendance: 1-2 days per week in the Nottingham office. Project duration: 6 months (with possible extension). Project Details: The project focuses on developing a forecasting solution for a large healthcare network. It uses historical clinic and marketing data to predict clinic usage and staffing needs, helping optimise scheduling and resource allocation. The goal is to build a scalable, data driven platform that improves operational efficiency. Responsibilities Design, train, and deploy ML models for time series forecasting and related data tasks Build and maintain data pipelines using cloud native tools (AWS, GCP, or Azure) Develop and optimise forecasting models (Prophet, ARIMA, LSTM, TimeGPT) Collaborate with data, product, and cloud engineers to deliver reliable, scalable solutions Participate in different stages of the project lifecycle - from discovery and PoC to production deployment, presenting your work to stakeholders Work closely with business stakeholders and SMEs to gather requirements, shape solutions, and drive project discovery Communicate modelling approaches, assumptions, and results to both technical and non technical audiences Essential knowledge, skills & experience (must have) 4+ years of commercial experience in Data Science / Machine Learning Strong hands on experience with Databricks: Notebooks, PySpark, Workflows, Deployment through Asset Bundles Proven experience building, deploying, and maintaining production ML solutions Broad experience across multiple ML domains, including: Forecasting / Time Series Modelling, Regression, Classification, Gradient Boosting models (e.g. XGBoost, LightGBM) Strong Python skills (Pandas, NumPy, scikit learn, PyTorch) Experience with model evaluation, performance monitoring, and accuracy metrics Version control (Git) Experience working with cloud environments (Azure preferred, AWS/GCP also considered) SQL Fluent English Nice to have Retail or similar consumer facing industry experience Azure DevOps: Repos, Boards, Pipelines Experience with Databricks model training and inference workflows Databricks Apps and Lakebase Experience with RAG pipelines Experience with vector databases (Weaviate, Milvus) Familiarity with LLM evaluation frameworks (e.g. DeepEval) Soft Skills Strong sense of ownership and accountability Strong stakeholder management skills Proactive attitude and ability to work independently Clear and confident communication with both tech and non tech stakeholders Comfortable working in ambiguity and helping define requirements Strategic thinking and focus on business impactTeam player Interview Steps GT interview with Recruiter Technical interview Final interview
25/06/2026
Full time
GT was founded in 2019 by a former Apple, Nest, and Google executive. GT's mission is to connect the world's best talent with product careers offered by high-growth companies in the UK, USA, Canada, Germany, and the Netherlands. Our clients operate in industries like healthcare, life sciences, fintech, retail, e-commerce, finance and many more - giving our team exposure to real world, high impact projects. About the Role We're looking for a Senior Data Scientist / ML Engineer to join a UK based client in the healthcare and pharmacy domain. The role combines forecasting and machine learning with end to end ownership of solution delivery, from project discovery and stakeholder collaboration through model development, deployment, and productionisation. Location: Nottingham, UK Office attendance: 1-2 days per week in the Nottingham office. Project duration: 6 months (with possible extension). Project Details: The project focuses on developing a forecasting solution for a large healthcare network. It uses historical clinic and marketing data to predict clinic usage and staffing needs, helping optimise scheduling and resource allocation. The goal is to build a scalable, data driven platform that improves operational efficiency. Responsibilities Design, train, and deploy ML models for time series forecasting and related data tasks Build and maintain data pipelines using cloud native tools (AWS, GCP, or Azure) Develop and optimise forecasting models (Prophet, ARIMA, LSTM, TimeGPT) Collaborate with data, product, and cloud engineers to deliver reliable, scalable solutions Participate in different stages of the project lifecycle - from discovery and PoC to production deployment, presenting your work to stakeholders Work closely with business stakeholders and SMEs to gather requirements, shape solutions, and drive project discovery Communicate modelling approaches, assumptions, and results to both technical and non technical audiences Essential knowledge, skills & experience (must have) 4+ years of commercial experience in Data Science / Machine Learning Strong hands on experience with Databricks: Notebooks, PySpark, Workflows, Deployment through Asset Bundles Proven experience building, deploying, and maintaining production ML solutions Broad experience across multiple ML domains, including: Forecasting / Time Series Modelling, Regression, Classification, Gradient Boosting models (e.g. XGBoost, LightGBM) Strong Python skills (Pandas, NumPy, scikit learn, PyTorch) Experience with model evaluation, performance monitoring, and accuracy metrics Version control (Git) Experience working with cloud environments (Azure preferred, AWS/GCP also considered) SQL Fluent English Nice to have Retail or similar consumer facing industry experience Azure DevOps: Repos, Boards, Pipelines Experience with Databricks model training and inference workflows Databricks Apps and Lakebase Experience with RAG pipelines Experience with vector databases (Weaviate, Milvus) Familiarity with LLM evaluation frameworks (e.g. DeepEval) Soft Skills Strong sense of ownership and accountability Strong stakeholder management skills Proactive attitude and ability to work independently Clear and confident communication with both tech and non tech stakeholders Comfortable working in ambiguity and helping define requirements Strategic thinking and focus on business impactTeam player Interview Steps GT interview with Recruiter Technical interview Final interview
Become a member of a team where you can contribute significantly to shaping the future of a world-renowned and influential company. Among top performers, you can make a direct and meaningful impact. As a Lead Engineer at JPMorgan Chase within our Market Data Services team you will play a pivotal role in designing, delivering and maintaining critical data distribution systems within the firm. These systems encompass both on-premises and cloud based infrastructure to deliver third party data to multiple lines of business. You will be working within an Agile project environment collaborating closely with cross-functional teams to deliver high-quality solutions to our clients. Job Responsibilities Applies deep technical expertise and problem-solving methodologies focused on analyzing complex data and systems, anticipating issues, considering upstream and downstream implications, and advising on mitigation actions Uses enterprise-authorized AI capabilities within the work environment to accelerate analysis of complex infrastructure signals and documentation of mitigation options, validating outputs and handling operational data according to sensitivity and security requirements. Designing and maintaining critical data delivery systems - encompassing both realtime data, historical data and AI/ML use-cases Collaboration with product owners and stakeholders to ensure data solutions align with business and regulatory requirements Capable of finding a balance between best of breed and cost effective solutions Act as a positive team player who is capable of accepting different intellectual points of view Clear and concise communicator; ability to present to senior management Ability to analyze and articulate problems and provide input into solutions Provide 3rd level support to operational roles A respect for strong process and control management disciplines Leads reuse-first adoption of AI-assisted practices across delivery and automation routines to reduce recurring issues, ensuring changes are validated, traceable and auditable, and aligned to resiliency and security expectations. Required qualifications, capabilities, and skills Formal training or certification on infrastructure engineering concepts and advanced applied experience in Cloud technologies including Kubernetes, Terraform and AWS Data Lake technologies (e.g. Snowflake, Databricks, AWS Glue/Athena, Lake Formation) Demonstrated experience using enterprise-authorized AI capabilities within the work environment to support infrastructure engineering workflows with strong validation habits and awareness of data sensitivity. Ability to review and validate AI-assisted recommendations before implementation, escalating when uncertain and ensuring outcomes align to resiliency, security, and auditability expectations Network architecture and protocols Programming languages (e.g. Java, Python, C++) Market Data / messaging products (e.g. TREP, Vela, RedLine, Bloomberg BPIPE, Solace, AMPS, etc.) Market Data vendors and their key products (e.g. Bloomberg, LSEG, Factset, S&P) Database technologies and SQL scripting Monitoring tools (ITRS Geneos, Dynatrace, Datadog)
25/06/2026
Full time
Become a member of a team where you can contribute significantly to shaping the future of a world-renowned and influential company. Among top performers, you can make a direct and meaningful impact. As a Lead Engineer at JPMorgan Chase within our Market Data Services team you will play a pivotal role in designing, delivering and maintaining critical data distribution systems within the firm. These systems encompass both on-premises and cloud based infrastructure to deliver third party data to multiple lines of business. You will be working within an Agile project environment collaborating closely with cross-functional teams to deliver high-quality solutions to our clients. Job Responsibilities Applies deep technical expertise and problem-solving methodologies focused on analyzing complex data and systems, anticipating issues, considering upstream and downstream implications, and advising on mitigation actions Uses enterprise-authorized AI capabilities within the work environment to accelerate analysis of complex infrastructure signals and documentation of mitigation options, validating outputs and handling operational data according to sensitivity and security requirements. Designing and maintaining critical data delivery systems - encompassing both realtime data, historical data and AI/ML use-cases Collaboration with product owners and stakeholders to ensure data solutions align with business and regulatory requirements Capable of finding a balance between best of breed and cost effective solutions Act as a positive team player who is capable of accepting different intellectual points of view Clear and concise communicator; ability to present to senior management Ability to analyze and articulate problems and provide input into solutions Provide 3rd level support to operational roles A respect for strong process and control management disciplines Leads reuse-first adoption of AI-assisted practices across delivery and automation routines to reduce recurring issues, ensuring changes are validated, traceable and auditable, and aligned to resiliency and security expectations. Required qualifications, capabilities, and skills Formal training or certification on infrastructure engineering concepts and advanced applied experience in Cloud technologies including Kubernetes, Terraform and AWS Data Lake technologies (e.g. Snowflake, Databricks, AWS Glue/Athena, Lake Formation) Demonstrated experience using enterprise-authorized AI capabilities within the work environment to support infrastructure engineering workflows with strong validation habits and awareness of data sensitivity. Ability to review and validate AI-assisted recommendations before implementation, escalating when uncertain and ensuring outcomes align to resiliency, security, and auditability expectations Network architecture and protocols Programming languages (e.g. Java, Python, C++) Market Data / messaging products (e.g. TREP, Vela, RedLine, Bloomberg BPIPE, Solace, AMPS, etc.) Market Data vendors and their key products (e.g. Bloomberg, LSEG, Factset, S&P) Database technologies and SQL scripting Monitoring tools (ITRS Geneos, Dynatrace, Datadog)
