Lead Software Engineer - Data Engineer

Corporate Technology at JPMorganChase builds and supports technology products that help power corporate functions across the network. On an agile team, you will contribute to trusted, secure, stable, and scalable engineering outcomes, with a role focused on production data pipelines and engineering practices including enterprise-authorized AI-assisted engineering.

What you’ll deliver

• Execute creative software solutions across design, development, and technical troubleshooting, using an approach that goes beyond routine problem-solving.
• Develop secure, high-quality production code, and contribute through code review and debugging of work completed by others.
• Lead the adoption of AI-assisted engineering practices that support better code quality, faster delivery, and improved operational outcomes, including AI-assisted code review/refactoring, test strategy acceleration, and incident/root-cause analysis support.
• Establish consistent validation standards across the team, including secure coding, peer review, and automated testing, and promote reuse of effective engineering patterns.
• Apply knowledge of the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to increase value from automation.
• Identify recurring remediation opportunities and drive elimination or automation of repeated issues to improve software and system operational stability.
• Lead evaluation sessions with external vendors, startups, and internal teams to test architectural designs and technical credentials for fit within existing systems and information architecture.

What you bring

• Formal training or certification in software engineering concepts and 5+ years of applied experience.
• Strong experience in Data Engineering with Python, SQL, and the AWS Tech Stack.
• Hands-on Python and Java development experience, including designing, building, and supporting production-grade applications and data pipelines.
• Strong SQL skills with experience working on data processing and data engineering workloads.
• Hands-on experience with AWS cloud services and building cloud-native solutions.
• Strong experience with Databricks, including development and processing of large datasets.
• Solid software engineering fundamentals and experience delivering and supporting solutions in a production environment.
• Demonstrated experience leading effective use of approved AI-assisted software development tools for coding, code review, test acceleration, and troubleshooting, plus the ability to set team expectations for validating AI 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, with experience coaching engineers on safe, compliant adoption within delivery practices.

Tools and technologies

Data Engineering, Python, SQL, AWS, Java, Databricks

Benefits

• Comprehensive health care coverage
• On-site health and wellness centers
• Retirement savings plan
• Backup childcare
• Tuition reimbursement
• Mental health support
• Financial coaching and more

Preferred capabilities

• Proficiency in automation and continuous delivery methods, with strong SDLC discipline including CI/CD, testing, code quality, and release controls.
• Advanced understanding of agile delivery, application resiliency, and secure engineering practices.

About the team

The Corporate Technology team depends on smart, driven people to develop applications and provide technology support for corporate functions across the network. Your work will contribute across Global Finance, Corporate Treasury, Risk Management, Human Resources, Compliance, Legal, and the Corporate Administrative Office, while aligning with the team’s technology controls agenda.

Location: Houston, TX (onsite).