Data Product Owner

Role overview Own a portfolio of data products that solve business problems for internal stakeholders and, in some cases, external audiences. Lead multiple cross-functional Scrum teams from discovery and prioritization through delivery and measurement, choosing an approach based on the outcome and building reusable foundations that help others create trusted data solutions.

Responsibilities - Set product vision, roadmap, and backlog priorities for data solutions, keeping teams focused on measurable business outcomes. - Lead day-to-day Agile work across multiple teams, including backlog refinement, sprint planning, prioritization, and blocker removal. - Turn stakeholder needs into clear problem statements, success measures, and acceptance criteria; track whether delivered solutions achieve their intended results. - Reconcile input from business intelligence and technical product leaders, surface conflicting priorities early, and guide decisions so delivery can continue. - Select suitable delivery methods for each problem, which may include dashboards, data platforms, AI-supported tools, or lightweight applications. - Build and maintain reusable data foundations, especially a governed semantic model, and enable self-service with documentation, patterns, and guardrails. - Monitor adoption, usage, and business impact; ensure solutions meet appropriate quality, security, privacy, release, and production-readiness expectations.

Requirements - Bachelor’s degree in a relevant field and at least seven years of product owner, product manager, analytics, BI, or equivalent experience. - Proven ability to lead Agile or Scrum teams, ideally with more than one team at a time. - Strong understanding of data and analytics products from source through consumption. - Track record of translating business needs into prioritized work, measuring outcomes, and communicating tradeoffs to technical and nontechnical stakeholders. - Ability to work effectively in a matrixed environment with changing priorities and direction.

Nice to have Experience in healthcare or another regulated industry; data governance, quality, or master data work; semantic modeling; Snowflake, Tableau, Python, or Streamlit; AI or large language model tools; and backlog management in Azure DevOps or similar systems. Familiarity with handling sensitive data, including protected health information, is a plus.

Benefits and work setup The listed pay range is $110,000–$140,000 per year, with the final offer dependent in part on location, experience, and skills. Applications are accepted until a candidate is selected.