VP Enterprise Data & Information Management
Regeneron
September 03, 2026
On-site
Tarrytown, NY
IT
Core Responsibilities
- Set enterprise data quality standards and governance policy; decide investments in master data management and cataloging.
- Ensure executive accountability for data governance outcomes; arbitrate trade-offs across business units.
- Define strategy and investment priorities for the enterprise semantic layer (centralized vs federated), ensuring semantic consistency as new AI capabilities/data products launch.
- Establish enterprise standards and investment priority for business glossary and taxonomy.
- Set enterprise strategy and investment case for knowledge graph infrastructure.
- Own enterprise architecture strategy for a federated, AI-ready data ecosystem, balancing domain data products with centralized governance and a graph-enabled semantic layer.
- Set GxP-compliant data standards and ensure regulated pipeline compliance; partner with Regulatory Affairs, Quality, and Legal.
- Set enterprise data privacy/security policy and risk tolerance; partner with CISO and Legal on privacy-by-design for architecture and access.
- Build and lead the multidisciplinary data organization (governance, engineering, metadata, architecture); hire/direct Executive Director, Enterprise Data; own multi-year enterprise data strategy and executive roadmap.
Qualifications
- BS/BA required.
- 20+ years leading enterprise data management/governance/architecture; building AI/analytics-ready data foundations.
- Expertise in governance, master/metadata management, and enterprise data quality (including building from scratch).
- Hands-on architectural depth in federated data architecture, semantic layers, and multimodal data infrastructure.
- Strong preference: GxP data compliance in life sciences/biopharma; governance intersecting with regulatory/clinical/commercial needs.
- Familiarity with AI data landscape (vector DBs, knowledge graphs, RAG, modern AI data platforms).
- Strong preference: governing standards with distributed teams (e.g., India).
- Ability to communicate/influence across Digital & Technology, business, science, Legal, and Regulatory Affairs; strong people leadership.
Application Instructions
- Apply now.
- Set enterprise data quality standards and governance policy; decide investments in master data management and cataloging.
- Ensure executive accountability for data governance outcomes; arbitrate trade-offs across business units.
- Define strategy and investment priorities for the enterprise semantic layer (centralized vs federated), ensuring semantic consistency as new AI capabilities/data products launch.
- Establish enterprise standards and investment priority for business glossary and taxonomy.
- Set enterprise strategy and investment case for knowledge graph infrastructure.
- Own enterprise architecture strategy for a federated, AI-ready data ecosystem, balancing domain data products with centralized governance and a graph-enabled semantic layer.
- Set GxP-compliant data standards and ensure regulated pipeline compliance; partner with Regulatory Affairs, Quality, and Legal.
- Set enterprise data privacy/security policy and risk tolerance; partner with CISO and Legal on privacy-by-design for architecture and access.
- Build and lead the multidisciplinary data organization (governance, engineering, metadata, architecture); hire/direct Executive Director, Enterprise Data; own multi-year enterprise data strategy and executive roadmap.
Qualifications
- BS/BA required.
- 20+ years leading enterprise data management/governance/architecture; building AI/analytics-ready data foundations.
- Expertise in governance, master/metadata management, and enterprise data quality (including building from scratch).
- Hands-on architectural depth in federated data architecture, semantic layers, and multimodal data infrastructure.
- Strong preference: GxP data compliance in life sciences/biopharma; governance intersecting with regulatory/clinical/commercial needs.
- Familiarity with AI data landscape (vector DBs, knowledge graphs, RAG, modern AI data platforms).
- Strong preference: governing standards with distributed teams (e.g., India).
- Ability to communicate/influence across Digital & Technology, business, science, Legal, and Regulatory Affairs; strong people leadership.
Application Instructions
- Apply now.