below marketmost similar roles pay hereabove market
This role pays more than
97%
of similar roles. Most pay
$204,525–$277,775
— the blue band above.
At the midpoint, this role pays about
$340k
versus about
$241k
for comparable roles.
Based on 240 similar postings.
Employer
About Regeneron
Regeneron is a leading science-driven biotechnology company that invents, develops, and commercializes life-transforming medicines for serious diseases.
Regeneron currently has
80 open roles
on FindRole.
Listed pay typically runs
$134,400–$241,200
across 50 roles with salary data.
The Executive Director: Data Management, Analytics, AI & Architecture will lead a unified Data Management and Architecture function within Global Development IT. This leader will integrate data engineering, analytics, and architecture capabilities into a single organization to define strategies for data platforms, AI architecture, and data governance. Key responsibilities include owning the end-to-end architecture strategy for data pipelines, establishing data stewardship, and ensuring regulatory compliance for clinical trial and safety data. The role requires expertise in cloud data platforms like AWS and Azure, as well as Snowflake and Databricks. Candidates must possess deep knowledge of data modeling, master data management, and GenAI architectural patterns. This position solves complex technical challenges regarding scalable, compliant data exchange and integration within a highly regulated life sciences environment.
Lead the unified Data Management & Enablement function by integrating data engineering, analytics, and architecture capabilities.
Define the end-to-end architecture strategy for data platforms, pipelines, and AI solutions within the vertical.
Drive the development of data platforms and standards to establish a validated, centralized data repository.
Build and scale a global data engineering and analytics team, including expanding capabilities in the India-based Global Capability Center.
Enforce data quality, lineage, and regulatory compliance standards such as GxP for clinical and safety data.
Establish data stewardship accountability and ensure consistent adoption of master data management and data catalog practices.
Represent the vertical at the Architecture Review Board to secure approval for technology investments and ensure enterprise alignment.
Communicate architecture tradeoffs and platform investment needs to senior business leadership and the Office of the CIO.
What we're looking for
Bachelor’s degree in Computer Science, Information Systems, Business Administration, or a related field.
Master’s degree (preferred).
17+ years of experience in product ownership or management roles focusing on enterprise platforms, PPM tools, TBM frameworks, and financial-based systems.
Experience in the biotech, pharma, or life sciences industry (preferred).
Track record of leading organizational integration or restructuring of technical functions.
Deep expertise in enterprise data architecture, data modeling, reference architecture design, and system integration strategies.
Hands-on experience with cloud data platforms (e.g., AWS, Azure) and modern data platforms (e.g., Snowflake, Databricks).
TOGAF, DAMA CDMP, PMP, or cloud platform certifications (preferred).
Data Architecture
Data Management
Machine Learning
Data Governance
Master Data Management
Cloud Data Platforms
Business Intelligence
Data Modeling
Data Quality
Agentic AI
Process Standardization
Automation
GxP
NIST AI RMF
ISO 42001
Data Governance
Artificial Intelligence
Machine Learning
Generative AI
Data Management
Risk Management
Cybersecurity
Data Privacy
AWS
Azure
Databricks
Data Quality
Access Management
Audit
Compliance
Microsoft Azure
Microsoft Fabric
Azure Databricks
MLflow
PyTorch
LangChain
Spark ML
Power BI
OneLake
Generative AI
MLOps
RAG
Infrastructure-as-Code
CI/CD
DataOps
Kotlin
Vector Search
Model Context Protocol
Data Governance
Generative AI
Agentic AI
Machine Learning
Advanced Analytics
AI Governance
Data Strategy
Responsible AI
Model Governance
Data Literacy
AI Assurance
Technology Policy
Algorithmic Accountability
Data Science
Computer Science