• Own the Pharmacy Data Product Portfolio (New + Legacy) • Define and manage a portfolio of pharmacy domain data products (e.g., prescription/refill journey, fulfillment milestones, operational status, member experience signals). • Identify and prioritize high-value legacy tables and datasets that have not been "productized" and are at risk during modernization. • Establish product roadmaps tied to measurable outcomes: improved self-service adoption, reduced time-to-insight, fewer data defects, and stronger downstream product enablement. • Lead product definition for data modernization efforts, ensuring legacy tables become managed data products, not unmanaged technical artifacts. • Partner with engineering and architecture to ensure migrated datasets include: Clear business definitions and consistent semantics Documented lineage and dependencies Versioning and change management expectations Validation and reconciliation criteria for cutover. • In collaboration with domain leaders, engineering, and data governance partners: Establish ownership and stewardship for important datasets (who owns, who approves changes, who resolves issues). • Create metadata and documentation standards (business glossary, dataset descriptions, field definitions, usage guidance). • Operationalize data quality management: Define critical data elements (CDEs) and quality rules Set thresholds/SLAs and issue management workflow Track and reduce recurring defects Define dataset lifecycle practices: retention, deprecation, and controlled evolution over time. • Improve accessibility and usability for analysts and associates by standardizing: Definitions, naming conventions, documentation, and examples Access patterns and secure sharing/entitlements "How to use" guidance and common query patterns. • Partner with digital and operational product teams to expose data appropriately. This exposure is achieved through product capabilities, such as convenient, reliable data products that represent "where a refill is in its journey" for web/mobile experiences. • Define and maintain data contracts and consumer expectations (availability, freshness, definitions, and schema evolution). • Operate within an Agile SAFe delivery model: Contribute to PI Planning, refinement, and ART ceremonies Write and manage Features (SAFe) and User Stories with clear acceptance criteria Maintain and prioritize a product backlog aligned to business outcomes and technical dependencies Coordinate cross-functionally across engineering, analytics, platform teams, compliance/security, and business stakeholders. • Track delivery progress and product KPIs (adoption, quality incidents, freshness, completeness, and consumer satisfaction).