Lead Software Engineer - Data Platform & Entitlements

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 Data Platform & Entitlements at JPMorganChase within the Commercial and Investment Bank, 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.

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 Creates secure and high-quality production code and maintains algorithms that run synchronously with appropriate systems 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. Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development Proactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture Required qualifications, capabilities, and skills Formal training or certification on software engineering concepts and 5+ years applied experience ( Strong knowledge and practical experience with Java, Spring Framework (Spring Boot, Spring MVC, Spring Data), RESTful APIs, Microservices architectures, and event streaming (Kafka) 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 Practical knowledge of CI/CD, Jenkins, and source code management tools such as Git and Bitbucket Proficiency in designing and implementing data models for relational databases. Experience working on Cloud platforms for compute and storage needs (AWS/GCP/Azure) In-depth knowledge of the financial services industry and their IT systems Practical cloud native experience Preferred qualifications, capabilities, and skills Experience with modern data platforms / data product engineering such as Databricks– Data Mesh, Unity Catalog, Lake house, Delta, Iceberg Hands-on experience with Spark and big data processing at scale Experience with Identity and Access Management platforms, role-based access control, or entitlement governance at scale Familiarity with authorization models – RBAC, ABAC, ReBAC, Policy and Authorization Engines, Propagation patterns – inheritance hierarchies, group level grants, row/column level security Exposure to IAM Concepts – SCIM, SSO/OIDC/SAML, service principals and how they map to data-layer permissions. Experience with LLMs, AI/ML platforms, or enterprise AI integration.