Associate Director, Data Strategy and Governance

Career Category Information Systems Job 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 .