Executive Director, Enterprise Data

Regeneron Pharmaceuticals•Tarrytown, GA

1d•$255,000 - $424,900•Hybrid

About The Position

Build our future together: At Regeneron, we use science and innovation to develop life-changing medicines for people with serious diseases. We're looking for an Executive Director of Enterprise Data to join our fast-moving Enterprise Data & AI organization. You'll be responsible for the integrity, accessibility, and governance of our enterprise data assets, making sure our proprietary scientific and clinical data is structured, governed, and ready for AI at scale. You'll build foundational data capabilities, from quality standards to the semantic layer that keeps definitions consistent across the company. This role reports to the VP, Enterprise Data & Information Management, and offers the chance to turn Regeneron's data into one of its biggest AI advantages.

Requirements

A Bachelor's degree in a related field (advanced degree required for certain scientific or clinical positions)
17+ years of experience in enterprise data management, data governance, or data architecture
Have built data foundations that enable AI and analytics at enterprise scale
Bring deep, hands-on experience with data governance, master data management, and metadata management
Can operate as both strategist and technical leader in federated data architecture and semantic layers
Understand how data governance intersects with regulatory, clinical, and commercial requirements
Stay current on the AI data landscape, including vector databases, knowledge graphs, and RAG
Have experience partnering with distributed engineering teams, including global delivery models
Communicate and build influence across technology, business, science, legal, and regulatory teams
Enjoy developing data engineering and governance talent across disciplines

Responsibilities

Enforce enterprise data quality standards, turning policy into day-to-day operating procedures
Lead master data management and data cataloging, keeping data assets inventoried and accessible
Own and run the enterprise semantic layer, keeping data definitions consistent across functions and AI systems
Build and maintain the enterprise business glossary and taxonomy
Lead development of knowledge graph infrastructure that supports advanced AI and scientific work
Design and deliver a federated, AI-ready data ecosystem across domains
Maintain GxP-compliant data standards, keeping regulated pipelines audit-ready
Own data privacy and security standards across the enterprise data estate