Product Manager IV

Product Data Manager

Duration: 12+ Months (Possible extension) Location: Washington, DC 20005 Onsite Role (4 days a week)

Responsibilities

• Looking for one senior person who operates simultaneously as a Product Owner for a data-intensive application, a Data Insights practitioner who can build and communicate what the data means, and a Testing leader who understands how every layer of the system fits together.
• These three dimensions are not separate jobs that happen to sit on the same org chart line.
• They are three lenses the same person applies to the same engagement, often in the same week.
• The person is embedded directly with a government client stakeholder and is the primary product and quality voice on the delivery.

Product Owner

• This person is the one writing epics and user stories from a deep understanding of a data-intensive pipeline - not from templates.
• Understand how data flows through the system, what business events trigger what processing steps, and how operations and engineering teams actually use the product.
• Run a backlog grooming session in the morning, walk a government client through a new screen in the afternoon, and write the acceptance criteria that locks the story that evening.
• Comfortable facilitating requirements sessions with program stakeholders who are not technical, translating what they hear into stories that engineering can build against and that testing can verify.
• A client says "I need to know why that account is unclaimed" and this person turns it into a defined data requirement, a dashboard feature, and a test scenario — without involving three other people to make that translation.

Data Insights and Data Science Practitioner

• Build when the situation requires it — writing SQL, using LLMs and AI assistance, building a dashboard view, or producing an analysis artifact that answers a specific program question.
• But their primary value is not raw technical output.
• Ability to look at a pipeline that moves millions of records, identify what the data is actually telling the program, and communicate that story in a way a government client can act on.
• They know what a meaningful metric looks like versus a vanity number.
• They can identify anomalies in processing output, frame them as program risk, and recommend a course of action.
• They have done this on data-intensive systems before, not on reporting layers built over clean warehouse data.
• The data in this context is messy, compliance-bound, and operationally consequential — they are comfortable in that environment.

Testing

• Understands the full quality picture from the inside out.
• They can read a batch execution log, write a database-level assertion, evaluate whether a security test is producing real evidence or just passing by coincidence, and hold a release gate when engineering wants to ship and the evidence is not there.
• They have been through at least one delivery cycle on a regulated system where a defect was not just a bug — it was a compliance finding — and they know what it means to produce a legally-retained release evidence package. They do not manage testers from a distance.
• They lead from the front, understand the technical controls that underpin each test stage, and are the single authority on whether the system is ready for production sign-off.