Lead Software Engineer - Data​/Technology

We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.

As a Lead Software Engineer at JPMorgan

Chase within the Commercial & Investment Bank - Digital & Platform Services team, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.

You will play a key role in building and evolving enterprise data products and strengthening our Data Engineering capabilities. This role requires a strong hands-on Data Engineer with deep experience in the Databricks ecosystem, enterprise-scale data platforms, and modern data engineering practices. You will contribute directly to solution design and implementation while providing technical leadership, establishing engineering patterns, and helping develop the broader team.

• Lead the design and development of scalable, reliable, and reusable enterprise data products.
• Provide hands-on technical leadership across solution design, implementation, code reviews, troubleshooting, and production readiness
• 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.
• Establish and promote effective Data Engineering patterns and standards across the team.
• Design solutions that support analytical, operational, reporting, and AI-driven use cases.
• Drive data quality, reliability, observability, governance, performance, and scalability across data products.
• Partner with architects, product teams, engineers, and data producers/consumers to translate business needs into sustainable data solutions.
• Mentor engineers and help build strong Data Engineering capability within the team.
• Identify opportunities to simplify platforms, improve engineering productivity, and increase reuse.

• Formal training or certification on software engineering concepts and 5+ years applied experience
• Minimum of 10+ years of software and/or data engineering experience building enterprise-scale solutions.
• Hands-on practical experience delivering system design, application development, testing, and operational stability
• Advanced in one or more programming language(s)
• 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
• Deep hands-on experience with Databricks and distributed data processing technologies.
• Strong programming and Data Engineering fundamentals with experience building…