Cloud Data Platform Lead 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

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.