Head of Data Product Management
Data Product Strategy & Vision
Define and champion the enterprise data product strategy, ensuring alignment with business goals, digital transformation priorities, and value roadmaps.
Develop a multi-year data product portfolio plan, identifying new opportunities, modernization needs, and rationalization paths.
Establish enterprise standards for evaluating data product investments, including expected value, feasibility, and adoption impact.
Business Alignment & Value Realization
Partner with senior business leaders to translate their priorities into actionable data product roadmaps.
Define KPIs, success metrics, and ROI models for every data product.
Ensure data products materially improve decision-making, operational efficiency, omnichannel performance, and AI readiness.
Product Leadership & Operating Model
Build and lead a high-performing Data Product Management team.
Define and institutionalize the enterprise data product lifecycle—from discovery to design, build, launch, iteration, and retirement.
Drive consistent, user-centric product design emphasizing reliability, clarity, trust, and accessibility.
Enterprise Collaboration & Orchestration
Partner across the Data & Analytics ecosystem:
- Data Engineering for scalable, performant data architectures.
- Data Governance to embed quality, lineage, compliance, and security.
- Analytics & AI to ensure data products power advanced modeling, automation, and generative AI use cases.
- Business Units to ensure strong adoption and continuous improvement.
- Serve as the alignment hub for priorities, standards, roadmaps, and delivery timelines.
Data Product Delivery & Continuous Improvement
Oversee delivery of high-quality, scalable data products.
Implement ongoing performance monitoring (availability, quality, usage, satisfaction, business outcomes).
Champion iteration and innovation through user feedback, usage insights, and emerging technology.
Governance, Standards & Risk Management
Ensure data products comply with enterprise governance, privacy, and regulatory standards.
Proactively manage data and operational risks in collaboration with legal, compliance, and security teams.
Promote responsible data usage and ethical AI practices.