Product Manager, Data Governance & Enterprise Data Products

Company Description

VERSANT (Nasdaq: VSNT) is an industry‑changing media and entertainment business and home to trusted brands that shape culture, inform audiences, and build lasting connections. It operates across four core markets: political news and opinion, business news and personal finance, golf, and sports and genre entertainment. These markets are served through a powerful portfolio of iconic and innovative brands, including CNBC, MS NOW, USA Network, Golf Channel, Oxygen, E!,

SYFY, and Versant’s sports division USA Sports, along with complementary digital assets including Fandango, Rotten Tomatoes, Golf Now and Golf Pass.

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.

• 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.

• 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, cataloguing, 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.

• 4+ years in product management, data product management, data governance, analytics product ownership, or enterprise data platform delivery.
• Experience with governed datasets, reporting assets, data catalogs, data quality capabilities, APIs, identity graphs, consumer data assets, or analytics platforms.
• Strong understanding of metadata, lineage, quality, stewardship, access controls, classification, retention, and policy enforcement.
• Experience working across data engineering, analytics, BI/reporting, privacy, security, compliance, marketing, product, and operations.
• Familiarity with consumer data and identity concepts, including profiles, consent, identifiers, audience attributes, segmentation, identity resolution, and activation controls.
• Ability to turn ambiguous business and governance needs into actionable roadmaps, requirements, and delivery plans.
• Bachelor's degree in business, computer science, information systems, data science, analytics, engineering, or equivalent experience.

• Experience in media, entertainment, advertising, streaming, subscription, digital products, or other consumer‑scale data environments.
• Familiarity with SQL, data modelling, warehouses, BI tools, data catalogs, observability,…