Product Manager, Data Governance & Enterprise Data Products

We are seeking a Product Manager focused on Data Governance and Enterprise Data Products to define and drive governance strategies that ensure data integrity, compliance, and accessibility across enterprise platforms and support key enterprise data products. This role partners with product, data engineering, analytics, privacy, compliance, and business teams to translate enterprise data needs into governed, high-quality data products that support confident decision-making and responsible activation.

The ideal candidate combines product management discipline with practical experience in data governance, metadata, data quality, reporting, consumer data, and identity.What You Will Own:Roadmap for governed datasets, reporting assets, metrics layers, consumer data products, identity signals, and downstream data consumption.Governance capabilities that make data discoverable, accurate, secure, compliant, documented, and fit for business use.Reporting trust across dashboards, executive reporting, canonical metrics, semantic layers, and self-service analytics.Alignment among business stakeholders, data producers and consumers, engineering, analytics, legal/privacy, security, and compliance.Responsibilities:Define product vision, success metrics, and roadmap for enterprise data governance and data product initiatives.Develop requirements, user stories, acceptance criteria, process flows, and release plans.Operationalize standards for metadata, business definitions, lineage, ownership, stewardship, classification, retention, quality, and access controls.Partner with engineering on ingestion, transformation, cataloging, quality monitoring, access provisioning, and change management.Partner with analytics and business teams on governed reporting datasets, canonical KPIs, semantic layers, and self-service experiences.Collaborate with privacy, legal, security, and compliance teams on consent, privacy-by-design, regulatory readiness, and appropriate consumer/identity data use.Drive adoption through communications, documentation, enablement, training, and launch planning.Track KPIs including data quality, catalog coverage, lineage completeness, access SLA performance, reporting accuracy, policy compliance, resolution time, and adoption.