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Head - Data Governance

Job in Morristown, Morris County, New Jersey, 07960, USA
Listing for: Sanofi
Full Time position
Listed on 2026-07-20
Job specializations:
  • IT/Tech
    Information Security & Data Protection, Information & Knowledge Management, Data Engineering, Data Warehousing
Salary/Wage Range or Industry Benchmark: 206250 - 297916 USD Yearly USD 206250.00 297916.00 YEAR
Job Description & How to Apply Below

Job Title

Head – Data Governance

Location

Morristown, NJ or Cambridge, MA

About the Job

Join the engine of Sanofi’s mission — where deep immunoscience meets bold, AI-powered research. In R&D, you’ll drive breakthroughs that could turn the impossible into possible for millions. You will join a strategic team within R&D Digital Data Office that coordinates cross‑R&D data governance, methodologies, processes, and frameworks for data collection and use, enabling data innovation, efficiency gains, and quality and compliance across R&D.

As the Head of Data Governance for R&D, you will serve as the strategic leader accountable for defining and orchestrating data governance frameworks and processes across the R&D organization, primarily focusing on clinical, portfolio, and CMC domains. You will define and champion the data playbook, frameworks, and change management strategy for the Federated DaaP (Data as a Product) operating model, enabling data transformation and AI‑at‑scale ambitions.

You will ensure all data usage remains compliant with data use policies and processes while maximizing value through cross‑functional collaboration with Digital R&D teams.

Main Responsibilities
  • Strategic Leadership & Framework Development
    • Define and orchestrate comprehensive data governance frameworks and best practices across clinical, portfolio, and CMC domains.
    • Champion the data playbook and Federated DaaP operating model, driving consistent and scalable governance practices.
    • Establish policies, standards, processes, and a data community of practice that embed governance into the fabric of R&D data management.
    • Define data best practices, frameworks, and guidelines to ensure consistent and effective data governance across the organization.
  • Data Excellence & FAIR Principles
    • Drive adherence to FAIR (Findable, Accessible, Interoperable, Reusable) data principles and processes to maximize data utility and value across the data lifecycle.
    • Implement robust data quality frameworks and data observability practices to ensure data is fit for purpose.
    • Establish data risk classification methodologies and business metadata standards that enable trusted, governed data consumption.
    • Drive data lineage, cataloging, and discoverability initiatives to enhance transparency and traceability.
    • Partner with business, legal, compliance, data privacy, cybersecurity, and digital teams to embed governance processes and frameworks.
    • Engage with data producers, consumers, and stewards across the R&D value chain to ensure governance frameworks are practical and business‑aligned.
    • Collaborate with development teams to adopt Governance as Code (GaaC) and AI‑powered governance tools that accelerate data capabilities, including data risk classification, business catalogues, data quality, and data observability.
    • Leverage automation and intelligent tooling to reduce manual governance overhead and increase scalability.
  • Change Management & Adoption
    • Lead the change management strategy for the federated data model and data community of practices, ensuring broad organizational adoption.
    • Foster a culture of data accountability, stewardship, and ownership across all levels of the organization.
    • Build and nurture cross‑functional data governance communities of practice that empower data producers, consumers, and stewards.
    • Drive stakeholder engagement and adoption through targeted communication, training, and enablement programs.
    • Establish metrics and KPIs to measure governance maturity, adoption, and business impact over time.
  • About You – Education & Experience
    • Bachelor’s degree required;
      Master’s degree preferred in Life Sciences, Data Science, Information Systems, Computer Science, or a related field.
    • 10+ years of progressive experience in R&D data governance, data lifecycle management, or related fields.
    • 5+ years in leadership roles within the pharmaceutical, biotechnology, or life sciences industry.
    Required Skills & Competencies
    • Proven track record of implementing data governance frameworks and processes that drive cross‑functional data trust, governance, and adoption in a regulated environment.
    • Experience governing large, complex data ecosystems in a regulated environment.
    • Strong…
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