Develops secure, high-quality software for banking data products, including migration, reconciliation, and data publishing tools. Responsibilities include system design, backend and ETL development, AWS cloud deployment, database development, testing, CI/CD, troubleshooting, architecture documentation, and data analysis. The role also promotes responsible AI-assisted development, contributes to engineering communities, and mentors or leads technical initiatives.
You’re ready to gain the skills and experience needed to grow within your role and advance your career — and we have the perfect software engineering opportunity for you
As a Software Engineer III at JPMorgan Chase as a part of the Data Product team within Consumer & Community Banking, you will contribute to a suite of tools designed for Consumer & Community Banking data analysts and publishing teams, offering seamless migration assistance, cross-platform reconciliation, and clear information on the data they need to make an impact.
Job responsibilities:
- Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
- Creates secure and high-quality production code and maintains algorithms that run synchronously with appropriate systems
- Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development
Gathers, analyzes, synthesizes, and develops visualizations from large, diverse data sets in service of continuous improvement of software applications and systems - Proactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture
- Contributes to software engineering communities of practice and events that explore new and emerging technologies
- 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.
- Adds to team culture of diversity, Opportunity, inclusion, and respect
Required qualifications, capabilities, and skills - Formal degree on Engineering and 6+ years applied experience
- Hands-on practical experience in system design, application development, testing, and operational stability
- Strong expertise in ETL development: PySpark, JavaSpark
- Solid experience with back-end development: Java, Python
- Hands on experience in building and deploying Cloud solutions with AWS
- Applied database experience with data models, SQL, DDL, DML on Snowflake & Iceberg
- Experience developing, testing, debugging, and maintaining code following best practices with stories, code repositories, and CI/CD pipelines
- Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, test creation, troubleshooting, or documentation) with demonstrated ability to critically evaluate, validate, and refine AI-generated outputs for correctness, performance, and security.
- Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; ability to guide peers on safe and effective usage within team practices.
- Overall knowledge of the Software Development Life Cycle
Preferred qualifications, capabilities, and skills
- Cloud/technical expertise: Strong knowledge of AWS/cloud services and solid understanding of software applications and technical processes within a technical discipline.
- Leadership & execution: Proven technical lead/mentor experience; effective in team settings while able to solve design/functionality problems independently with minimal oversight.
- Domain & communication: Banking domain experience (incl. working with data engineers/analysts) preferred, plus strong written and verbal communication across management levels and business partners.
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