VP Enterprise Data & Information Management

Regeneron Pharmaceuticals•Tarrytown, GA

5d•Onsite

About The Position

Regeneron's Enterprise Data & AI organization is newly established and moving fast, built to drive AI transformation and adoption at scale across every part of the enterprise. This is a high-visibility, high-velocity position where the work is directly tied to business and scientific impact. The VP of Enterprise Data & Information Management is the guardian of Regeneron's most differentiated AI asset: our data. This role ensures Regeneron's data advantage, anchored by Regeneron's proprietary scientific and clinical assets and external data partnerships, is structured, governed, and AI-ready at enterprise scale. This leader will ensure the integrity, accessibility, and governance of Regeneron's enterprise data assets and enterprise data products. The VP of Enterprise Data & Information Management will build Regeneron's enterprise data program from the ground up and establish foundational data capabilities and governance structures. This leader will set and enforce enterprise data quality standards, policies, and compliance requirements; manage the enterprise data catalog, metadata infrastructure, and semantic layer; partner with business units to mature data as a foundational and differentiating capability for AI at scale; ensure compliant, GxP-ready data pipelines; and build the federated multimodal infrastructure that makes production-grade AI possible. Data must be not just available, but trustworthy, traceable, and ready for enterprise AI use.

Requirements

BS/BA degree in a related field required.
20+ years leading enterprise data management, data governance, or data architecture organizations, with a demonstrated track record of building data foundations that enable AI and analytics at scale.
Deep expertise in data governance frameworks, master data management, metadata management, and enterprise data quality, including experience establishing these disciplines from scratch in a complex enterprise.
Hands-on architectural depth in federated data architecture, semantic layers, and multimodal data infrastructure. Able to operate as both strategist and technical leader.
Experience with GxP data compliance in a regulated life sciences or biopharma environment strongly preferred.
Understanding how data governance intersects with regulatory, clinical, and commercial data requirements.
Deep familiarity with the current AI data landscape: vector databases, knowledge graphs, retrieval-augmented generation, and modern data platforms that support enterprise AI workloads.
Experience partnering with distributed engineering organizations.
Successful experience governing data standards and architecture with a team in India or similar global delivery model is strongly preferred.
Ability to communicate and influence effectively across Digital & Technology, business units, scientific functions, Legal, and Regulatory Affairs.
Strong people leadership. Experience building and developing senior data engineering and governance talent in a competitive market.

Responsibilities

Sets the enterprise data quality standard and governance policy for Regeneron's data estate, and decides where the organization invests in master data management and cataloging capability to meet it.
Holds executive accountability for data governance outcomes across the enterprise, arbitrating trade-offs when data quality priorities compete with delivery timelines across business units.
Sets the strategic direction and investment priority for the enterprise semantic layer, deciding which domains and data models are standardized centrally versus federated to business units.
Holds enterprise accountability for semantic consistency as new AI capabilities and data products are introduced, resolving definitional conflicts that cross functional lines.
Sets the enterprise standard and investment priority for Regeneron's business glossary and taxonomy program, determining which domains require centrally governed vocabulary.
Sets the enterprise strategy and investment case for knowledge graph infrastructure, prioritizing which domains and use cases justify the build.
Owns the enterprise architecture strategy for a federated, AI-ready data ecosystem, setting the standards that balance domain-owned data products against centralized governance and a graph-enabled semantic layer.
Sets enterprise policy for GxP-compliant data standards and holds executive accountability for regulated data pipeline compliance across the data layer.
Owns the executive relationship with Regulatory Affairs, Quality, and Legal leadership on GxP and data privacy requirements, escalating emerging regulatory risk to the SVP, Chief AI Officer.
Sets enterprise policy and risk tolerance for data privacy and security across the data estate and holds executive accountability for Regeneron's data protection posture.
Owns the executive relationship with the CISO organization and Legal on privacy-by-design strategy for data architecture and access patterns.
Builds, develops, and leads a multidisciplinary data organization spanning data governance, data engineering, metadata management, and data architecture, including hiring and directing the Executive Director, Enterprise Data, and setting the multi-year strategy the organization executes against.
Sets the standard for how data infrastructure must be buildable, scalable, and maintainable at platform level, and owns the handoff model between data strategy and data engineering execution.
Represents the enterprise data strategy and roadmap to executive leadership, holding ultimate accountability for the data foundation across Enterprise Data & AI. Partners with peers across Enterprise Data & AI to ensure the data foundation is integrated with AI delivery, governance, and enablement functions.