Lead Software Engineer - Data Platform & Entitlements

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As a Lead Software Engineer Data Platform & Entitlements at JPMorgan

Chase 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

• 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

• 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 -…