Associate Director, Data Strategy and Governance

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