Associate Director, Data Governance, FAIR, and AI-Readiness
Amgen
August 21, 2026
Remote friendly (United States)
United States
IT
Associate Director, Data Governance, FAIR, and AI-Readiness
Key Responsibilities:
- Lead enterprise Data Governance, FAIR, and data product strategy and roadmap, aligning investments to scientific and business priorities.
- Establish a value-realization framework to measure outcomes, adoption, and ROI.
- Execute the Enterprise Data Strategy: data ownership, reusable data products, lifecycle management, data contracts, and adoption measures.
- Evolve federated governance with clear decision rights, ownership/stewardship accountabilities, councils, standards, and escalation paths.
- Evolve FAIR maturity across the enterprise (data lifecycle, metadata standards, persistent identifiers, controlled vocabularies, access patterns).
- Advance active metadata, data catalog, lineage, business glossary, semantic and knowledge graph capabilities.
- Set governance policies/controls for quality, observability, privacy, security, retention, and responsible use for regulated and AI-enabled use cases.
- Partner with Data Architecture, Data Engineering, Digital, Security, Privacy, Legal, and business teams to operationalize governed data products.
- Enable responsible AI by defining and enforcing data readiness criteria.
- Serve as data engagement lead for an assigned business function to drive adoption of FAIR.
- Manage large-scale data programs and communicate outcomes, risks, dependencies, and value to senior leadership.
Basic Qualifications:
- Doctorate + 2 years Data Management/Information Systems (or related), OR Master’s + 6 years, OR Bachelor’s + 8 years, OR Associate + 10 years.
Mandatory Skills/Qualifications:
- Biotech/pharma experience with regulated data and compliance requirements.
- Leadership of enterprise data governance/data management/active metadata/data quality/data product initiatives.
- Hands-on FAIR expertise (active metadata, standards, semantics, interoperability, access controls).
- Experience establishing governance operating models (ownership, stewardship, policy/standards/controls, issue management).
- Strong stakeholder management, communication, and influencing skills.
Preferred Skills/Qualifications:
- Experience implementing enterprise data strategy, scaling FAIR, data product operating model, and data contracts.
- Knowledge of active metadata/observability/lineage/ontologies/knowledge graphs/policy-as-code.
- Experience with tools (e.g., Collibra, Databricks Unity Catalog, Reltio, SciBite, TopQuadrant).
- Responsible AI experience (ML/GenAI/RAG/AI agents data readiness).
- Ability to define measurable outcomes (adoption, quality, time-to-discovery, reuse, compliance, AI readiness).
- Experience managing external partners and distributed teams.
Benefits (Total Rewards Plan; eligibility-based):
- Health and welfare plans, retirement/savings plan, financial plans, work/life balance, career development; includes medical/dental/vision, life/disability, flexible spending accounts; annual bonus/incentives (as applicable); stock-based long-term incentives; time-off; flexible work models where possible.
Application Instructions:
- Apply now; no application deadline—applications are accepted until sufficient applicants or a candidate is selected; sponsorship not guaranteed.
Key Responsibilities:
- Lead enterprise Data Governance, FAIR, and data product strategy and roadmap, aligning investments to scientific and business priorities.
- Establish a value-realization framework to measure outcomes, adoption, and ROI.
- Execute the Enterprise Data Strategy: data ownership, reusable data products, lifecycle management, data contracts, and adoption measures.
- Evolve federated governance with clear decision rights, ownership/stewardship accountabilities, councils, standards, and escalation paths.
- Evolve FAIR maturity across the enterprise (data lifecycle, metadata standards, persistent identifiers, controlled vocabularies, access patterns).
- Advance active metadata, data catalog, lineage, business glossary, semantic and knowledge graph capabilities.
- Set governance policies/controls for quality, observability, privacy, security, retention, and responsible use for regulated and AI-enabled use cases.
- Partner with Data Architecture, Data Engineering, Digital, Security, Privacy, Legal, and business teams to operationalize governed data products.
- Enable responsible AI by defining and enforcing data readiness criteria.
- Serve as data engagement lead for an assigned business function to drive adoption of FAIR.
- Manage large-scale data programs and communicate outcomes, risks, dependencies, and value to senior leadership.
Basic Qualifications:
- Doctorate + 2 years Data Management/Information Systems (or related), OR Master’s + 6 years, OR Bachelor’s + 8 years, OR Associate + 10 years.
Mandatory Skills/Qualifications:
- Biotech/pharma experience with regulated data and compliance requirements.
- Leadership of enterprise data governance/data management/active metadata/data quality/data product initiatives.
- Hands-on FAIR expertise (active metadata, standards, semantics, interoperability, access controls).
- Experience establishing governance operating models (ownership, stewardship, policy/standards/controls, issue management).
- Strong stakeholder management, communication, and influencing skills.
Preferred Skills/Qualifications:
- Experience implementing enterprise data strategy, scaling FAIR, data product operating model, and data contracts.
- Knowledge of active metadata/observability/lineage/ontologies/knowledge graphs/policy-as-code.
- Experience with tools (e.g., Collibra, Databricks Unity Catalog, Reltio, SciBite, TopQuadrant).
- Responsible AI experience (ML/GenAI/RAG/AI agents data readiness).
- Ability to define measurable outcomes (adoption, quality, time-to-discovery, reuse, compliance, AI readiness).
- Experience managing external partners and distributed teams.
Benefits (Total Rewards Plan; eligibility-based):
- Health and welfare plans, retirement/savings plan, financial plans, work/life balance, career development; includes medical/dental/vision, life/disability, flexible spending accounts; annual bonus/incentives (as applicable); stock-based long-term incentives; time-off; flexible work models where possible.
Application Instructions:
- Apply now; no application deadline—applications are accepted until sufficient applicants or a candidate is selected; sponsorship not guaranteed.