Data Product Manager

The Data Product Manager will help AHEAD turn its data into trusted, discoverable and reusable products that solve business problems. Reporting to the Director, Data Platform, this role works with Data Platform engineering, Analytics and domain teams to set priorities, define requirements and help consumers use data effectively.

This is a hands‑on individual‑contributor role. You will work directly with consumers, examine existing data assets, define useful products, maintain product documentation and catalog content, and help teams deliver and improve those products throughout their lifecycle.

Governance is an essential part of the role: making sure consumers understand what a product means, whether they can trust it, and how to access and use it appropriately. Your governance responsibilities cover data products delivered or published through the Data Platform, within existing enterprise policies. You will apply agreed policies through practical product standards and discovery workflows, partnering with engineering, Security and domain owners on supporting controls.

Product discovery, strategy and prioritization

• Work with business stakeholders, analysts, application teams and other data consumers to understand their decisions, workflows and unmet needs; distinguish a reusable data product opportunity from a one‑off reporting or integration request.

• Define product problems, target consumers, expected value and success measures, evaluating existing assets for reuse before proposing new development.

• Own the data product roadmap and product priorities within the strategy and capacity agreed with the Director, Data Platform; balance business value, urgency, risk, dependencies and ongoing support costs.

• Own product goals, priorities and requirements; partner with the Product Owner, who manages day‑to‑day backlog coordination, intake and delivery dependencies, using one shared backlog.

Product delivery and lifecycle

• Translate consumer needs into engineering‑ready requirements and acceptance criteria covering business definitions, data scope and granularity, freshness, quality, access and supported consumption methods.

• Partner with Data Platform engineers, Analytics and source‑system teams to scope practical releases, resolve dependencies, validate outputs with consumers and communicate delivery trade‑offs.

• Manage the product lifecycle from discovery through launch, adoption, improvement and retirement, including change communication and the impact of schema or definition changes on consumers.

• Partner with Analytics and domain owners to identify authoritative business definitions and align reusable datasets and semantic models, preserving useful existing capabilities and resolving inconsistencies where they matter.

Governance and product trust

• Define and apply lightweight product publication and readiness standards, including accountable owners, business definitions, classification, source and lineage information, quality and freshness expectations, access instructions and lifecycle status.

• Establish named business/domain owners who remain accountable for data meaning, quality expectations and appropriate‑use or access decisions within policy. Coordinate stewardship and document those decisions.

• Define governance and access requirements with Security, IAM and engineering, including approval paths, sensitive‑data protections and traceability; validate that delivered products meet the agreed requirements.

• Prioritize quality and governance improvements based on consumer impact and risk. Engineers implement the supporting checks, monitoring, lineage capture and technical controls.

Discovery, self‑service and adoption

• Maintain a useful inventory of data products and directly create…