openleverjobgether
Dir, Innovative Enterprise Data Product Lead
Jobgether
LocationUS
EmploymentFull-time
Posted2026-08-24T11:14:46.050000+00:00
Last observed2026-08-26 21:51:40.410433
Job idjobgether-jobgether:lever:627bc874-f6d7-4ca6-8179-695ef7748d91
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Dir, Innovative Enterprise Data Product Lead based in United States. The Director, Innovative Enterprise Data Product Lead will shape the strategy and evolution of enterprise data foundations that enable trusted, reusable, and AI-ready data products. The role owns key capabilities spanning reference data, master data, metadata, data standards, stewardship, and business definitions. You will define product vision, roadmaps, priorities, adoption strategies, and value measures that improve data trust, consistency, discoverability, and interoperability across the enterprise. A key focus will be transforming foundational data assets into innovative products enriched with business meaning, semantic definitions, rules, metrics, lineage, metadata, and context. Working across business, analytics, technology, governance, and data enablement teams, you will translate strategic priorities into scalable and reliable capabilities. The role offers significant influence in a complex, matrixed environment where strong product leadership and stakeholder management are essential to driving adoption and measurable business value. This is an opportunity to build foundational capabilities that accelerate analytics, enable AI-driven solutions, and establish stronger enterprise-wide data practices. Own the product strategy, roadmap, prioritization, and lifecycle management for enterprise reference data, master data, metadata, and data standards. Define innovative data products that incorporate business meaning, semantic definitions, reusable measures, standards, metadata, lineage, and clear consumption patterns. Partner closely with data enablement teams to translate product strategy into executable delivery plans, align priorities, remove operational barriers, and ensure scalable and reliable enterprise capabilities. Collaborate with business, analytics, technology, governance, operations, and data product teams to identify high-value capabilities, prioritize investments, and reduce duplication across the organization. Drive product adoption through stakeholder engagement, clear consumption models, communication strategies, and continuous enhancement based on user needs and feedback. Establish product standards, governance routines, intake processes, service expectations, and value measures that support reliability, reuse, compliance, scalability, and measurable business impact. Define and maintain product requirements around data quality, metadata coverage, lineage, standards adoption, stewardship, and semantic consistency. Translate complex business and data requirements into clear product priorities and actionable roadmaps. Monitor product performance, adoption, risks, dependencies, and business outcomes, using insights to guide prioritization and continuous improvement. Influence senior stakeholders and cross-functional teams to align enterprise data investments with broader strategic and business objectives. Requirements Bachelor’s degree in a related field required; a Master of Science and/or MBA is strongly preferred. 10+ years of experience in pharmaceuticals, healthcare, technology, data, analytics, consulting, or a related environment, with significant experience in data products, data strategy, product management, or analytics enablement. 5+ years of specialized experience in reference data, master data, metadata management, data standards, data governance, stewardship, semantic models, product management, or AI-ready data foundations. Demonstrated ability to define product vision, roadmaps, prioritization frameworks, use cases, adoption strategies, value measures, and governance routines within complex matrixed organizations. Strong understanding of semantic data products, business definitions, data quality, metadata, lineage, standards, stewardship, and AI-ready data consumption patterns. Proven experience pa
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