Data Product Owner Role

Data Product Owners turn data assets into products people can understand, trust, and use. They set the direction for datasets, dashboards, APIs, analytical services, and other data capabilities, then keep delivery focused on the users and mission outcomes those products are meant to serve.

The work combines discovery, prioritization, and delivery. Data Product Owners learn how users make decisions, translate those needs into a roadmap and an ordered backlog, define acceptance criteria, and work with engineers, analysts, designers, governance specialists, and program leaders through release and adoption. They make hard tradeoffs visible and keep asking whether the product is producing value, not merely whether the team shipped it.

What you’ll build

• Product visions and roadmaps that connect user needs, agency priorities, and measurable outcomes.
• Prioritized backlogs, user stories, acceptance criteria, and release plans that give delivery teams clear decisions.
• Discovery and feedback practices that bring users into product development before and after release.
• Measures of adoption, quality, timeliness, usability, and mission value that guide the next investment.
• Working agreements across engineering, analytics, governance, security, and program teams so ownership remains clear from idea through operation.

Who you are

You are energized by the space between a promising idea and a product that earns regular use. You listen closely, decide clearly, and can say no, not yet, or not this way while keeping stakeholders focused on the outcome.

You are fluent enough in data and delivery to work on substance with technical teams, but you never lose sight of the people using the product. You treat the roadmap as a living set of choices, not a ceremonial plan.

• A working foundation in product ownership or product management, including discovery, roadmaps, backlog management, and iterative delivery.
• The ability to turn user and stakeholder needs into clear requirements, user stories, acceptance criteria, and priorities.
• Enough data fluency to discuss schemas, data quality, analytics, interfaces, and technical tradeoffs with delivery teams.
• Experience using qualitative and quantitative evidence to evaluate adoption, usability, and outcomes.
• The judgment and communication skills to make tradeoffs in regulated or mission-critical environments where accountability matters.