Product Manager, Data & Analytics

The Product Manager – Data & Analytics will own the product-side data lifecycle for Universal+—from event taxonomy and instrumentation to validated, decision-grade datasets. The Product Manager – Data & Analytics will also ensure privacy alignment, data governance, and trusted, consistent, verifiable data across all sources, including partner integrations, analytics, attribution, and customer engagement platforms. This role will also manage gate releases on data readiness and uphold data standards across the product. Responsibilities: Data Contracts & Instrumentation: Define and maintain event taxonomy, tagging plans, and data contracts across platforms (mobile/CTV/web), partner SDKs/APIs, attribution, and engagement platforms; version and document schemas. Data Quality Ownership: Establish data SLOs (Service Level Objectives) for coverage, accuracy, and freshness; run pre-/post-release instrumentation QA, reconciliations (e.g., entitlements vs. events), anomaly alerts, and a data defect log with SLAs (Service Level Agreements) to resolution. QoE Monitoring: Define and monitor Quality of Experience (QoE) telemetry and thresholds (e.g., playback errors, start-up time, buffering, ad experience) and coordinate remediation with the Product Owner, QA, and partners/vendors. Integration Stewardship: Partner with internal teams, vendors, and distribution partners to ensure implementations meet data requirements (identity/consent propagation, campaign/offer attribution, metadata mapping). Attribution & Engagement Flows: Own product requirements for attribution and lifecycle messaging data flows (link routing, campaign parameters, event pass-through, audience syncs) to ensure reliable downstream analytics. Delivery & Governance: Run the data workstream plan and RAID (Risks, Assumptions, Issues, Dependencies); gate launches on data readiness (Definition of Ready/Done for tracking). Translate privacy policies (consent, retention/deletion, IRR—Individual Rights Requests) into technical requirements and tests. Data Handoffs: Publish validated datasets, lineage, and documentation; align on KPI definitions and data availability/freshness expectations; support ad hoc investigations into data integrity. Vendors & Tooling: Lead evaluations/PoCs for analytics, tag management, attribution, and observability/monitoring tools; manage integration roadmaps and deprecation/change control with partners and vendors. Data Compliance: Ensure adherence to company data management standards, data deletion requirements, and data retention policies.