Lead Data Engineer

JPMorgan Chase & Co.; Greater London; On-site; GBP 110,000 - 150,000; Full time

Job summary

JPMorgan Chase & Co. is seeking a Lead Data Engineer in London to design, build, and operate a cloud-native data platform powering analytics and regulatory reporting. You will deliver scalable data pipelines, drive engineering standards, and mentor a team within Personal Investing.

You will work with modern data lakehouse patterns, implement IaC, and collaborate across product, analytics, and engineering groups to translate business needs into robust designs.

Qualifications

• Degree in Computer Science or STEM field.
• 8 years of hands-on professional experience coding as a data engineer.
• Strong software engineering fundamentals and end-to-end development lifecycle.

Responsibilities

• Design scalable, reusable data processing and data quality frameworks using Python, PySpark, and dbt.
• Build and optimize batch and streaming data pipelines with high performance and observability.
• Develop and operate workflow orchestration with Apache Airflow to schedule and monitor data movements.
• Model and transform data for analytics using SQL and dbt to support BI and reporting.
• Write production-grade Python/PySpark code with testing and maintainable design.
• Implement infrastructure-as-code (Terraform) to provision cloud data platform components.
• Containerize and deploy services using Docker and Kubernetes.
• Collaborate with analysts, data scientists, and product teams to translate requirements into designs.
• Own critical data systems to improve reliability, security, and operations.
• Mentor junior engineers and influence technical direction.

Job description

• Locations 1 Cabot Square, London, E14 4QJ, GB
• Job Schedule Full time

Job Description

Shape how hundreds of thousands of UK investors use data to make confident, informed investment decisions. Join a team building modern, cloud-native data platforms that enable analytics, regulatory reporting, and data-driven products at scale. You’ll work with contemporary lakehouse and streaming patterns, strong engineering practices, and a culture that values ownership and continuous improvement. This role offers meaningful scope to influence platform standards and mentor others while growing your technical and leadership impact.

As a Lead Data Engineer at JPMorgan Chase within Personal Investing, you will design, build, and operate a robust cloud-native data platform and pipelines that power analytics, regulatory reporting, and data-promoten applications. You will help us deliver reliable, scalable, observable, and secure data solutions by applying strong software engineering fundamentals and modern data engineering patterns. You’ll work closely with partners across product, analytics, and engineering to translate business needs into resilient technical designs. You’ll also contribute to engineering excellence through best practices, mentoring, and thoughtful technical direction.

Job responsibilities

• Design scalable, reusable data processing and data quality frameworks using Python, PySpark, and dbt
• Build and optimize batch and streaming data pipelines with strong performance, fault tolerance, and observability
• Develop and operate workflow orchestration (e.g., Apache Airflow) to schedule, monitor, and manage data movement and transformations
• Model and transform data for analytics using SQL and dbt to support business intelligence and reporting workloads
• Write production-grade Python/PySpark code with disciplined testing, performance tuning, and maintainable object-oriented design
• Implement infrastructure-as-code (e.g., Terraform) to provision and manage cloud-based data platform components
• Containerize and deploy services using Docker and Kubernetes (and related tooling such as Helm)
• Collaborate with analysts, data scientists, and application teams to turn requirements into technical designs and delivered solutions
• Own critical data systems by improving reliability, scalability, security, and operational excellence
• Mentor junior engineers and influence the team’s technical direction through standards, reviews, and knowledge sharing
• Uses enterprise-authorized AI capabilities within the work environment to accelerate data platform and model design analysis and documentation, validating outputs and handling data according to sensitivity and security requirements
• Applies reuse-first, AI-assisted practices within delivery and operational routines (e.g., backup/recovery validation and access control review support), ensuring traceability/auditability and alignment to resiliency and security expectations

Required qualifications, capabilities, and skills

• Degree in Computer Science or a STEM-related field (or equivalent)
• Demonstrated experience delivering in an agile, fast-paced engineering environment
• 8 years of recent, hands-on professional experience actively coding as a data engineer
• Strong software engineering fundamentals (system design, data structures, object-oriented programming, testing strategies, and end-to-end development lifecycle)
• Strong Python programming skills, including unit and integration testing
• Hands-on experience building and operating cloud-based data platforms using major cloud services (e.g., AWS, Google Cloud, or Azure)
• Experience with large-scale distributed data processing and performance tuning
• Hands-on experience with modern data warehousing/lakehouse technologies (e.g., Redshift, BigQuery, Snowflake; and engines such as Spark, Flink, or Trino; and table formats such as Iceberg, Hudi, or similar)
• Strong SQL skills and experience with SQL-based transformation tooling (e.g., dbt)
• Experience designing and operating orchestration pipelines using Airflow or similar tools
• Experience designing and building streaming pipelines using Kafka, Pub/Sub, or similar messaging systems
• Demonstrated experience using enterprise-authorized AI capabilities within the work environment to support data engineering workflows with strong validation habits and awareness of data sensitivity
• Ability to review and validate AI-assisted outputs (e.g., model/design summaries or operational checklists) before use, escalating when uncertain and following data handling requirements

Preferred qualifications, capabilities, and skills

• Data modeling experience for analytics and reporting use cases
• Knowledge of security, risk, compliance, and governance considerations for data platforms
• Experience building continuous integration and continuous delivery automation for data and platform services
• Experience with container-based deployment environments (Docker, Kubernetes, etc.)
• Demonstrated ability to coach teammates on engineering practices and contribute to a collaborative, inclusive team culture

About Us

J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world’s most prominent corporations, governments, wealthy individuals and institutional investors. Our first-class business in a first-class way approach to serving clients drives everything we do. We strive to build trusted, long-term partnerships to help our clients achieve their business objectives.
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs. Visit ourFAQs for more information about requesting an accommodation.

About the Team

Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we’re setting our businesses, clients, customers and employees up for success.