Job detail for 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 **

• 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

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