JPMorgan Chase—Lead Software Engineer-Java, Spring Boot

Job description

Description: We have an exciting and rewarding opportunity for you to take your software engineering career to the next level. As a Lead Software Engineer at JPMorgan Chase within the Data Platform team, you'll design and deliver scalable data pipelines, backend services, and infrastructure-as-code that support large-scale revenue and analytics processing. Job responsibilities: - Design, build, and maintain production-grade ETL/data pipelines using PySpark, AWS Glue, and Apache Iceberg. - Develop and operate backend microservices and APIs (Java/Spring Boot, Python). - Write clean, well-tested, maintainable code with strong unit and integration test coverage. - Build and manage infrastructure-as-code and CI/CD pipelines (Jenkins, Spinnaker, Terraform/CloudFormation). - Optimize data workflows for performance, cost, and reliability. Collaborate with data engineers, analysts, and product stakeholders to translate requirements into robust solutions. - Participate in design and code reviews; troubleshoot production issues and drive root-cause fixes. Mentor junior engineers and contribute to engineering best practices. - Leverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity across complex deliverables (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards; contributes learnings and reusable patterns to improve broader team effectiveness. - 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 Required qualifications, capabilities, and skills - Bachelor's degree in Computer Science, Engineering, or related field (or equivalent experience). - 5+ years of professional software engineering experience. - Strong proficiency in at least one of Python or Java, plus solid software design fundamentals. - Hands-on experience with AWS cloud services (S3, Glue, Lambda, IAM, RDS/Aurora). - Experience building data pipelines and working with SQL and relational databases (e.g., PostgreSQL). - Familiarity with distributed data processing (Spark) and data lake/table formats. - Proficiency with Git-based workflows and CI/CD practices. - Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security. - Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices - Strong testing discipline (unit, integration) and debugging skills. - Background in financial, revenue, or large-scale analytics data domains. Preferred Qualifications - Experience with Apache Iceberg or similar transactional table formats. - Experience with workflow orchestration (Airflow) and containerization (Docker). - Experience with infrastructure-as-code and pipeline tooling (Jenkins, Spinnaker, Terraform).