Associate Director, Data Governance, FAIR, and AI-Readiness
RemoteUnited States
Job Summary
Lead enterprise Data Governance, FAIR data practices, and data product strategy, aligning investments to scientific and business priorities. Establish a value-realization framework to measure outcomes and ROI, then execute the Enterprise Data Strategy including ownership, reusable products, lifecycle management, and adoption measures. Evolve a federated governance operating model with clear decision rights, stewardship accountabilities, and data councils while advancing FAIR maturity through metadata, lineage, and semantic interoperability. Set policies for data quality, observability, privacy, and security to enable responsible AI. Partner with Data Architecture, Engineering, Security, and business teams to operationalize governed data products and drive adoption across domains. Manage large-scale programs and external partners, communicating risks and value to senior leadership.
Required Qualifications
- Doctorate degree and 2 years of Data Management, Information Systems, or related experience
- Master's degree and 6 years of Data Management, Information Systems, or related experience
- Bachelor's degree and 8 years of Data Management, Information Systems, or related experience
- Associate degree and 10 years of Data Management, Information Systems, or related experience
- Experience in the biotechnology or pharmaceutical industry
- Understanding of regulated data, business processes, and compliance requirements
- Demonstrated leadership of enterprise data governance, data management, active metadata, data quality, or data product initiatives across business and technology teams
- Hands-on understanding of FAIR data principles and their practical application through active metadata, standards, semantics, interoperability, and access controls
- Experience establishing data governance operating models, including data ownership, stewardship, policy, standards, controls, and issue management
- Strong stakeholder management, communication, and influencing skills
- Ability to translate complex data topics into business value and decisions
Desired Qualifications
- Experience implementing enterprise data strategy
- Scaling FAIR
- Data products operating model
- Data contracts
- Knowledge of modern data management capabilities, including active metadata, data observability, lineage, ontologies, knowledge graphs, and policy-as-code
- Experience with master data, data catalog, governance, quality, active metadata, and semantic technologies: Collibra, Databricks Unity Catalog, Reltio, SciBite, or TopQuadrant
- Experience enabling responsible AI, including data readiness for machine learning, generative AI, retrieval-augmented generation, and AI agent use cases
- Ability to define measurable outcomes for data investments, including data product adoption, quality, time-to-discovery, reuse, compliance, and AI readiness
- Experience managing external partners and geographically distributed delivery teams in complex stakeholder environments
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