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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Associate Director, Data Governance, FAIR, and AI-Readiness - **Company:** Amgen - **Location:** Washington, DC, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Big Data, Information Systems, Data Architecture, Information Engineering, Data Governance, Graph Database, Interoperability, Machine Learning, Metadata, Metadata Repositories, Metadata Standards, DataOps, Policy as Code, Retrieval-Augmented Generation, Generative AI, Data Strategy, Collibra, Data Management, Virtual Agents, Databricks - **Published:** August 18, 2026 - **Apply:** https://www.dcjobsite.com/job.asp?id=3357952855&tx=KJ3939FFF&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54 ## About the Role Doctorate degree and 2 years of Data Management, Information Systems, or related experience OR Master's degree and 6 years of Data Management, Information Systems, or related experience OR Bachelor's degree and 8 years of Data Management, Information Systems, or related experience OR Associate degree and 10 years of Data Management, Information Systems, or related experience, * Experience in the biotechnology or pharmaceutical industry, with an 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, with the ability to translate complex data topics into business value and decisions. Preferred Skills and Qualifications * Experience implementing enterprise data strategy, scaling FAIR, data products operating model, and 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. ## Description * Lead the enterprise Data Governance, FAIR, and data product strategy and roadmap, aligning investments to scientific and business priorities. * Establish a value-realization framework to measure business outcomes, adoption, and return on investment from data initiatives. * Execute the Enterprise Data Strategy, including data ownership, reusable data products, lifecycle management, data contracts, and adoption measures. * Evolve a federated governance operating model with clear decision rights, data ownership, stewardship accountabilities, data councils, data standards, and escalation paths. * Evolve FAIR maturity across the enterprise, including embedding FAIR practices in the data lifecycle, metadata standards, persistent identifiers, controlled vocabularies, and access patterns. * Advance active metadata, data catalog, lineage, business glossary, semantic and knowledge graph capabilities to improve discovery, context, interoperability, and trust. * Set governance policies and controls for data quality, observability, privacy, security, retention, and responsible use; ensure fit-for-purpose data 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 across platforms and domains. * Enable responsible AI by defining and enforcing data readiness criteria. * Serve as the data engagement lead for an assigned business function, driving adoption of data management practices, including FAIR, to deliver measurable data improvements and business value. * Manage large-scale data programs, cross-functional initiatives, and external partners; communicate outcomes, risks, dependencies, and value realization to senior leadership. ## Related Videos - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [Blueprints for Success: Steering a Global Data & AI Architecture](https://www.wearedevelopers.com/videos/1577-blueprints-for-success-steering-a-global-data-ai-architecture) - [Big Business, Big Barriers? 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