JPMorgan Chase
Technical Product Manager - Data Products
$133K–$215K
New York, NY · Manager · Full-time · Posted Oct 14, 2026
- Experience
- 5+ years applied experience in product engineering concepts; other specific experience durations are listed in requirements.
- Education
- Advanced degree preferred; formal training or certification on product engineering concepts required.
About the job
Own the lifecycle of data, analytics, and AI-enabled products, translating business and technical needs into governed, scalable data capabilities.
What you'll do
- Set product vision, roadmaps, objectives, and adoption measures; manage Agile delivery and releases.
- Analyze APIs, application services, and data structures; build data pipelines and prototypes, and design data models.
- Develop semantic and AI-enabled retrieval workflows, while embedding quality, lineage, security, and regulatory controls.
What they ask for
- Formal training or certification on product engineering concepts.
- 3+ years delivering digital, data, analytics, or technology products in financial services, consulting, technology, or another highly regulated industry.
- 3+ years hands-on with SQL, Python, and PySpark; cloud data warehouses and lakes; and analysis of application services, APIs, and JSON structures.
- 2+ years in logical and physical data modeling and polyglot data modeling; 3+ years project management using Agile delivery tools; demonstrated deployment of enterprise generative AI and agentic solutions.
Nice to have
- Advanced degree in Data Science, Information Systems, or a closely related discipline.
- Experience with semantic retrieval, tool orchestration, model evaluation or explainability, data mesh, Apache Iceberg, or regulated financial services governance.
Pay
USD 133,000.00-$215,000.00 base salary
Tools
Jira, Jira Align, SQL, Python, PySpark, Apache Iceberg
AI focus
Develop and deploy enterprise generative AI and agentic solutions integrated with enterprise data, APIs, security controls, and monitoring; develop semantic retrieval workflows, agentic interfaces, tool orchestration, and model context protocol services.
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