Lead Scala/Java Software Engineer - CDAO Data Platforms

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 JPMorganChase within the Data Platforms team in the Chief Data & Analytics Office, 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. Your knowledge of Scala, functional programming and agentic techniques will help our team meet the requirements of our diverse user base. Your work will be intellectually challenging ranging from meta-programming, domain specific languages and interpreter design to delivery of services and user interfaces all via public cloud.

Leads the engineering of cutting-edge solutions in the areas of metadata, meta-modelling and distributed systems. Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or breakdown technical problems Develops secure and high-quality production code, and reviews and debugs code written by others 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. Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems

Required qualifications, capabilities, and skills

Formal training or certification on software engineering concepts and advanced applied experience Hands-on practical experience delivering system design, application development, testing, and operational stability Applied experience in Scala and Java Experience working with asynchronous runtimes like Cats Effect 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 Proficient in all aspects of the Software Development Life Cycle Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security In-depth knowledge of the financial services industry and their IT systems Practical cloud native experience

Preferred qualifications, capabilities, and skills

Meta-programming through libraries such as shapeless or Magnolia.

Doman Specific Language design and interpretation

Knowledge of domain driven design

Proficient with SQL/No-SQL databases