Lead Software Engineer - Data Technology | Data Engineering

JPMorgan Chase & Co.
United States
3 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Working hours
Regular working hours

Tech stack

Java (Programming Language) Artificial Intelligence Airflow Amazon Web Services Automation of Tests Cloud Computing Software Quality Code Review Databases Continuous Integration Information Engineering Extract Transform Load (ETL)
+31 more
Database Queries Software Debugging Distributed Computing Environment Python (Programming Language) Machine Learning Software Tools Search Technologies Secure Coding Software Engineering Technical Data Management Systems Strategies of Testing Toolchain Data Logging GitHub Copilot Large Language Models Snowflake Data Build Tool (dbt) Prompt Engineering Fastapi Data Lakes Pyspark Apache Flink Maintaining Code AWS Data Analytics Apache Kafka Video Streaming Cloudwatch Code Restructuring Data Pipelines Programming Languages Control M

Job description

As a Lead Software Engineer - Data Engineering at JPMorgan Chase within the Consumer & Community Banking/Data Products team, you serve as a seasoned member of an agile team to design and deliver trusted market-leading technology products in a secure, stable, and scalable way. You are responsible for carrying out critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives., * Design, develop, and optimize large-scale ETL (Extract Transform Load) data pipelines.

  • Build high-quality Python applications using modular code, reusable components, logging, and automated testing.
  • Develop and maintain distributed data processing solutions using PySpark.
  • Large scale end-to-end testing design and validation.
  • Implement and support workflow orchestration using Control-M or Apache Airflow (MWAA).
  • Develop cloud-native solutions leveraging AWS services, including Glue, Athena, Lambda, and CloudWatch.
  • Design and manage modern data lake architectures utilizing Iceberg and/or Delta Lake.
  • Administer and optimize Snowflake environments, including streams, tasks, roles, and warehouses.
  • Participate in code reviews and champion engineering best practices, testing standards, and CI/CD processes.
  • Leverage approved AI-assisted development tools while ensuring secure, responsible, and compliant software delivery.

Requirements

  • Formal training or certification on software engineering concepts and 5+ years applied experience with a strong focus on data engineering.
  • Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages - Python (primary) & Java (secondary)
  • Hands-on experience with PySpark or other distributed data processing frameworks.
  • Strong expertise in DBT (Data Build Tool) and modern ETL (Extract Transform Load) development practices.
  • Experience with workflow orchestration platforms such as Control-M or Apache Airflow (MWAA).
  • Expertise with AWS data services, including Glue, Athena, CloudWatch, and Lambda.
  • Knowledge of modern open table formats such as Iceberg and/or Delta Lake.
  • Experience with Snowflake administration and development.
  • Strong SQL skills and experience with modern database technologies.
  • Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.
  • Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.

Preferred qualifications, capabilities, and skills

  • Experience with Kafka, Flink, or other streaming technologies.
  • Familiarity with AI/ML technologies including LLMs, prompt engineering, vector search, and responsible AI practices.
  • Experience using AI-assisted software development tools such as GitHub Copilot, Claude, or similar technologies.
  • Financial services industry experience and understanding of large-scale enterprise data environments.
  • Experience mentoring engineers and leading technical delivery initiatives.

Benefits & conditions

We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.

About the company

Chase is a leading financial services firm, helping nearly half of America’s households and small businesses achieve their financial goals through a broad range of financial products. Our mission is to create engaged, lifelong relationships and put our customers at the heart of everything we do. We also help small businesses, nonprofits and cities grow, delivering solutions to solve all their financial needs.

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Apply on jpmc.fa.oraclecloud.com
Prepare application

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