Associate Director, Data Strategy and Governance

Career CategoryInformation SystemsJob Description
Job description for Associate Director – Data Strategy in Data Foundation and Governance
The Associate Director, Enterprise Data Strategy & AI Enablement, is responsible for shaping and executing the enterprise-wide data strategy that accelerates AI adoption, digital transformation, and business value realization across the organization.
This role serves as a strategic bridge between Business, Data, Technology, Analytics, and AI teams to establish an AI-ready data ecosystem built on trusted data products, active metadata, semantic knowledge layers, governance by design, and modern data management practices.
The leader will drive enterprise data maturity, define future-state capabilities, enable responsible AI, and create measurable business outcomes through data and AI investments.
Key Responsibilities
· Contribute to defining and evolve the Enterprise Data & AI-readiness Strategy aligned with business priorities and digital transformation goals
· Drive FAIR maturity assessments and continuous improvement programs
· Partner with business leaders to identify strategic opportunities where data and AI can create competitive advantage
· Help in creation and execution of multi-year data strategy execution roadmap for Amgen
covering Data Products, Data Governance, Enterprise Master data, Metadata management, Reference data including Ontologies and Knowledge Graphs, Data Quality and Data observability
· Establish and drive adoption of enterprise-wide frameworks for modern data management practices such as AI-ready data, data products, context engineering, unstructured data, and semantic modelling
· Define data product lifecycle, ownership, governance, funding, and value realization frameworks
· Establish and operationalize enterprise Data Product Management capabilities
· Enable domain-centric data ownership and scalable data product delivery models
· Define enterprise framework for measuring Return on Data and AI-readiness Investments with outcomes clearly linked to KPIs around revenue growth, cost optimization, productivity gains, business adoption, and impact
· Develop executive dashboards highlighting value realization from strategic data initiatives
· Help modernize governance from policy-driven to intelligence-driven governance
· Drive modernization of structured and unstructured data management capabilities
· Contribute to defining the target-state architecture required to support Generative AI, Agentic AI, Predictive AI, and Advanced Analytics
· Implement governance-by-design principles leveraging automation and active metadata
· Partner with Legal, Privacy, Compliance, and Risk teams to establish AI-readiness controls, Data Ethics, Regulatory compliance frameworks
· Identify and develop pilots for emerging technologies and trends in areas such as Agentic AI, Autonomous data management, augmented data quality, Active metadata, and data observability
· Drive Data management pilots, MVPs, and innovation initiatives that demonstrate measurable business value
· Build enterprise capabilities for AI-enabled data management operations
· Influence executive stakeholders and build alignment across global teams.
· Serve as a trusted advisor to senior leadership on data and AI-readiness strategy
· Promote a culture of innovation, experimentation, and data-driven decision making
· Mentor and develop next-generation data and AI leaders
· Represent the organization in industry forums and external thought leadership initiatives
Preferred Qualifications
· 16 to 20 years of experience in Data Management, Data Strategy, Analytics, or Digital Transformation
· 5+ years leading enterprise-scale Data and AI transformation initiatives.
· Experience in Life Sciences, Healthcare, Pharmaceutical, or highly regulated industries preferred.
· MBA or Masters in relevant field preferred
· Excellent stakeholder management and communication skills
· Demonstrable experience in value articulation of data management initiatives
· Exposure to complex stakeholder ecosystem
· Strong expertise in several of the following:
· Enterprise Data Strategy
· Data Governance
· Data Products
· Master Data Management
· Metadata Management
· Reference data management and Knowledge Graphs
· Data Quality & Observability
· Unstructured Data Management
· AI & Modern Data Capabilities
· Good knowledge of one or multiple Data Management platforms such as Collibra, Informatica, Ataccama, Reltio, Centree, DataBricks etc.
· Basic understanding of Generative AI, Agentic AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Semantic Layer Architecture, Active Metadata Platforms
.