
Associate Director, Data Strategy and Governance
Amgen · India - Hyderabad · Onsite
- Pharmaceuticals & Biotech
- 10,001+ employees
- Thousand Oaks, CA
Strong hiring record · median 29 days open
All reasons
In its favour
- Still listed on the employer's own board
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
.
Skills
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