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Regeneron Pharmaceuticals

Develops biopharmaceutical therapies for serious diseases

VP Enterprise Data & Information Management

Data ManagementConfirmed live in the last 24 hours
Full-timeTarrytown, NY, USANo salary listed

About the Job

Requirements

  • A BS/BA degree in a related field is 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; ability to operate as both strategist and technical leader.
  • Deep familiarity with the current AI data landscape, including vector databases, knowledge graphs, retrieval-augmented generation, and modern data platforms that support enterprise AI workloads.
  • Ability to communicate and influence effectively across Digital & Technology, business units, scientific functions, Legal, and Regulatory Affairs.
  • Strong people leadership and experience building and developing senior data engineering and governance talent in a competitive market.

Responsibilities

  • Build the enterprise data program from the ground up and establish foundational data capabilities and governance structures.
  • 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 federated multimodal infrastructure for production-grade AI.
  • Own the multi-year enterprise data strategy and executive accountability for its delivery, including hiring and directing the Executive Director, Enterprise Data, who leads day-to-day governance and engineering execution.
  • Set enterprise data quality standards and governance policy, and decide investment in master data management and cataloging capabilities.
  • Hold executive accountability for data governance outcomes across the enterprise and arbitrate trade-offs between data quality priorities and business-unit delivery timelines.
  • Set strategic direction and investment priorities for the enterprise semantic layer, including decisions on centrally standardized versus federated domains and data models.
  • Hold enterprise accountability for semantic consistency as AI capabilities and data products are introduced, resolving definitional conflicts across functional lines.
  • Set enterprise standards and investment priorities for the business glossary and taxonomy program, determining which domains require centrally governed vocabulary.
  • Set enterprise strategy and investment case for knowledge graph infrastructure, prioritizing domains and use cases.
  • Own enterprise architecture strategy for a federated, AI-ready data ecosystem, balancing domain-owned data products with centralized governance and a graph-enabled semantic layer.
  • Set enterprise policy for GxP-compliant data standards and hold executive accountability for regulated data pipeline compliance.
  • Own executive relationships with Regulatory Affairs, Quality, and Legal leadership on GxP and data privacy requirements, escalating emerging regulatory risk to the SVP, Chief AI Officer.
  • Set enterprise policy and risk tolerance for data privacy and security and hold executive accountability for the organization's data protection posture.
  • Own the executive relationship with the CISO organization and Legal on privacy-by-design strategy for data architecture and access patterns.
  • Build, develop, and lead a multidisciplinary organization spanning data governance, data engineering, metadata management, and data architecture; hire and direct the Executive Director, Enterprise Data, and set the multi-year strategy the organization executes against.
  • Set standards for data infrastructure to be buildable, scalable, and maintainable at platform level, and own the handoff model between data strategy and data engineering execution.
  • Represent the enterprise data strategy and roadmap to executive leadership and hold ultimate accountability for the data foundation across Enterprise Data & AI.
  • Partner with peers across Enterprise Data & AI to integrate the data foundation with AI delivery, governance, and enablement functions.

Desired Qualifications

  • Experience with GxP data compliance in a regulated life sciences or biopharma environment, including understanding how data governance intersects with regulatory, clinical, and commercial data requirements.
  • Successful experience governing data standards and architecture with a distributed engineering organization, including a team in India or a similar global delivery model.

About the Company

Regeneron Pharmaceuticals

Develops biopharmaceutical therapies for serious diseases

Regeneron Pharmaceuticals develops and commercializes medicines for serious diseases, with a focus on cancer, eye diseases, allergic and inflammatory diseases, and infectious diseases. Its products come from using proprietary research capabilities and technologies to discover and develop therapies, often in collaboration with academic, research, and industry partners. Revenue comes from selling approved medicines and from licensing its technologies and entering co-development and co-commercialization partnerships. The company works with healthcare providers and regulators to ensure treatment delivery and safety. Its goal is to improve patient outcomes by bringing life-transforming medicines to market through rigorous R&D and strategic collaborations, maintaining leadership in biopharmaceutical innovation.

Company size
10,001+
Company stage
IPO
Headquarters
Town of Mount Pleasant, New York
Founded
1988

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