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