Description
We are seeking a Sr. Data Product Leader to support our office. As a Sr. Data Product Leader, you will own the day-to-day execution of treating data as a managed, governed, and intentionally designed product across the HPEFS digital ecosystem.
Responsibilities
- Own the data product vision, strategy, and roadmap for HPEFS, aligned to enterprise data-as-a-product direction and broader digital strategy.
- Define and maintain the enterprise data product portfolio across key business domains.
- Translate business needs, AI/analytics use cases, and reporting requirements into outcome-based data product requirements.
- Prioritize the portfolio based on business value potential, reuse, risk reduction, and enablement of downstream analytics, automation, and AI use cases.
- Own the full data product lifecycle from ideation and design through development, deployment, adoption, iteration, and deprecation.
- Ensure data products are reusable, composable, and scalable across consumption channels.
- Ensure HPEFS data products are intentionally designed to support AI, advanced analytics, operational reporting, executive dashboards, automation, and digital product consumption.
- Serve as the business-side steward of data governance for assigned domains.
- Partner with Business Product Managers, Business Analysts, and Process Engineering so data products support end-to-end process and product outcomes.
- Define and track KPIs for each data product, including adoption, data quality, consumer satisfaction, time-to-insight, reuse, and business value delivered.
Education and Experience Required
- First-level university degree or equivalent experience; advanced university degree preferred.
- Typically 7+ years of related experience in product management, data management, or data strategy.
- Prior people management experience required.
- Demonstrated experience treating data as a product.
Knowledge and Skills
- Strong understanding of data governance, data quality, metadata, lineage, and data catalog concepts.
- Ability to define AI-ready data product requirements.
- Understanding of responsible AI principles.
- SQL proficiency and working familiarity with modern data platforms.
- Familiarity with AI/ML data consumption patterns, semantic layers, feature stores, vector databases, data APIs, or model-ready datasets.
What We Can Offer You:
- Comprehensive suite of benefits that supports physical, financial, and emotional wellbeing.
- Investment in your career through specific programs catered to helping you reach career goals.
- Unconditional inclusion and celebration of individual uniqueness.