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JPMorgan Chase & Co. VERIFIED EMPLOYER

Senior Data Engineer III.

Data Engineering & Architecture Full-Time
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Senior Data Engineer III: our view in 3 lines...

  • The Role:This role is for a senior data engineer building cloud-native data platforms and pipelines for analytics, regulatory reporting, and data-driven applications.
  • The Person:The person will build and maintain data processing frameworks, batch and streaming pipelines, data models, workflow orchestration, cloud infrastructure, and containerized services.
  • Requirements:The role requires five years of hands-on coding as a data engineer, with Python programming, SQL skills, cloud technologies, orchestration tools, infrastructure-as-code, and enterprise-authorized AI capabilities.

About the role

As a Data Engineer JPMorgan Chase within Personal Investing, you will build and operate a robust cloud-native data platform and pipelines that power analytics, regulatory reporting, and data-driven applications at scale. You will help us deliver reliable, scalable, observable, and secure data solutions across cloud-native services, lakehouse architectures, data warehousing, and streaming systems. You’ll partner with teammates to build consistent, maintainable pipelines and contribute across the software delivery lifecycle from requirements through support.

Job responsibilities

  • Build and maintain scalable, reusable data processing and data quality frameworks using Python, PySpark, and dbt
  • Build and operate batch and streaming data pipelines with strong scalability, performance, and fault tolerance
  • Develop and manage workflow orchestration using tools such as Apache Airflow to support reliable, observable, and well-scheduled data movement and transformations
  • Implement and optimize data models and warehouse structures to support analytics and business intelligence workloads
  • Write clean, testable Python/PySpark code using object-oriented principles and unit testing
  • Implement infrastructure-as-code for the data platform using Terraform
  • Containerize and deploy services using Docker, Kubernetes, and Helm
  • Contribute across the software development lifecycle, including requirements, design, development, testing, deployment, release, and support
  • Collaborate with teammates in an agile, dynamic environment to deliver reliable outcomes

 

Required qualifications, capabilities, and skills:

  • Degree in Computer Science or a STEM-related field (or equivalent practical experience)
  • Agile environment experience working in dynamic settings
  • Software development lifecycle expertise (requirements, design, architecture, development, testing, deployment, release, and support)
  • 5+ years hands-on coding as a data engineer
  • Cloud technologies proficiency (e.g., AWS, Google Cloud, or Azure)
  • Python programming (object-oriented principles, unit/integration testing)
  • SQL skills and familiarity with SQL-based workflow tools (e.g., dbt)
  • Orchestration tools experience (e.g., Airflow or similar)
  • Messaging/streaming systems understanding (e.g., Kafka or Pub/Sub)
  • Infrastructure-as-code familiarity (e.g., Terraform) for cloud-based data infrastructure
  • Enterprise-authorized AI capabilities usage to support data engineering workflows, including validation habits, data sensitivity awareness, and ability to review and validate AI-assisted outputs before use, escalating when uncertain and following data handling requirements

 

Preferred qualifications, capabilities, and skills

  • Data modeling skills
  • Experience with data streaming and scalable processing frameworks (e.g., Spark, Flink, Beam, or similar)
  • Experience automating deployment, releases, and testing in continuous integration and continuous delivery pipelines
  • Experience with lakehouse patterns and table formats (e.g., Apache Iceberg)
  • Experience with federated query engines such as Trino
  • Experience designing automated tests (unit, component, integration, and end-to-end), including use of mocking frameworks
  • Experience with containers and container-based deployment environments (e.g., Docker, Kubernetes, or similar)

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 our FAQs for more information about requesting an accommodation.

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.

Published August 17, 2026
Location London, United Kingdom
Category Data Engineering & Architecture  
Job Type Full-Time  

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