Global Banking Data Services Product Manager - Vice President

JPMorgan Chase JPMorgan Chase · Banking · OH · Commercial & Investment Bank

Product Manager (VP) for Global Banking Data Services, focusing on API-first data services built on Snowflake, Databricks, Starburst, and Postgres. The role involves defining strategy, roadmap, and delivery of these services, ensuring governed and reliable data consumption across the firm, with capabilities leveraging REST API, OpenSearch, Cortex Search, Kafka, and MCP. Emphasis on API product ownership, agile delivery, platform enablement, and strong governance, risk, and controls.

What you'd actually do

  1. Contribute to the multi-quarter product vision, roadmap, and OKRs for GB Data Services (API products, onboarding patterns, search/retrieval experiences).
  2. Contracts/schemas, versioning, backward compatibility, authn/authz, entitlements, audit logging, and deprecation strategy.
  3. Maintain and prioritize the backlog in JIRA; author epics/features/stories with clear acceptance criteria and outcomes.
  4. Partner with engineering/architecture to deliver APIs over Snowflake/DBx/Starburst/Postgres (performance, resiliency, and cost-to-serve considerations).
  5. Embed data governance, metadata, lineage, and data quality into the product operating model.

Skills

Required

  • 7+ years (or equivalent) in Product Management / Product Ownership for enterprise platforms or services in a complex environment.
  • Strong API product management experience (lifecycle, standards, adoption, operational metrics).
  • Working fluency with modern data platforms and consumption patterns across Snowflake, DBx (Databricks), Starburst, and Postgres.
  • Familiarity with search/retrieval systems (REST API, OpenSearch and/or Cortex Search) and how they support data discovery/consumption.
  • Experience supporting analytics/AI-enabled workflows, including Cortex Analyst-style experiences and integration patterns with MCP.
  • Proven ability to operate in Agile delivery, manage JIRA backlogs, and translate ambiguous requirements into shippable increments.
  • Strong controls mindset: data governance, data quality, metadata, and secure handling of sensitive data.

Nice to have

  • Experience building self-service data access platforms (guided intake, automated provisioning, data dictionary/catalog integration).
  • Track record driving SLOs/SLAs, reliability/observability, incident/problem management, and cost optimization for data services.
  • Experience with federated/distributed data access patterns and performance tuning across multiple backends.

What the JD emphasized

  • firm control standards
  • regulatory/control requirements
  • governance, risk & controls
  • data governance
  • secure handling of sensitive data