Associate Director, Semantic Data & Knowledge Strategy

Location: Hyderabad (Office)

Job Description Summary

Location: Hyderabad, India #LI-Hybrid

Internal job title: Associate Director, PO&CF Data Enablement

About the Role

The Associate Director, PO&CF Data Enablement will lead the strategy, governance, adoption, and value realization of enterprise data enablement capabilities across People & Organization (P&O) and Corporate Functions.

The role will be responsible for establishing AI-ready, analytics-ready, and business-consumable data ecosystems through semantic technologies, metadata management, ontologies, knowledge graphs, enterprise taxonomies, data products, and knowledge management frameworks.

This role serves as a strategic bridge between business stakeholders, Enterprise Data Management, Data Governance, Data & AI teams, and technology organizations to ensure enterprise knowledge and data assets are discoverable, trusted, reusable, and consumable for Analytics, GenAI, Agentic AI, Semantic Search, Knowledge Discovery, and Decision Intelligence use cases.

Key Responsibilities

Data Enablement Strategy & Roadmap: define and execute the PO&CF Data Enablement strategy and roadmap, driving enterprise adoption of Semantic Layer, metadata and knowledge management, and AI-ready data capabilities. It will establish standards for data discoverability, interoperability, governance, and reuse, while building a long-term roadmap to enable AI, Analytics, Reporting, Knowledge Management, and Agentic AI initiatives and accelerate business outcomes through trusted, governed, and reusable data and knowledge assets.

Semantic Layer & Knowledge Architecture Leadership: own the Semantic Layer strategy, governance, and adoption across PO&CF, driving the development of enterprise knowledge models, semantic assets, ontologies, taxonomies, and knowledge graphs. It will establish semantic frameworks that connect structured and unstructured data, integrate metadata, semantic technologies, knowledge graphs, and AI-ready architectures into the enterprise data ecosystem, and promote reusable business concepts and knowledge assets across domains.

Metadata, Knowledge Management & Governance: drive enterprise metadata management and governance, leveraging platforms such as Collibra to lead ontology development, taxonomy management, business glossary governance, and knowledge modelling. It will establish consistent standards for business definitions, controls, policies, data, and knowledge assets, while partnering with Enterprise Data Management and business stakeholders to strengthen data discoverability, consistency, and trust across the organization.

AI, GenAI & Agentic AI Enablement: Enable enterprise AI and Agentic AI capabilities by establishing governed semantic assets and AI-ready knowledge frameworks that support copilots, assistants, intelligent agents, and semantic search. It will drive the adoption of RAG and GraphRAG architectures, partner with Data Science, Analytics, and AI teams to accelerate enterprise AI initiatives, and ensure knowledge assets can be effectively consumed across modern AI platforms and agentic ecosystems.

Business Domain Enablement: Partner with business leaders and SMEs to model and govern knowledge across P&O and Corporate Functions; Drive semantic enablement and business knowledge management across People & Organization (P&O), Legal, Security & Information Security, Ethics, Risk & Compliance (ERC), Environmental, Social & Governance (ESG),Corporate Affairs, Internal Audit, Corporate Communications and selected Finance domains

Stakeholder Engagement & Value Realization: Engage senior leaders across P&O and Corporate Functions, partnering closely with EDM, Architecture, Security, Compliance, Data Governance, Analytics, and AI organizations to drive strategic alignment and successful delivery. It will define KPIs, adoption metrics, and value realization measures, while leading organizational change management and capability adoption; support strategic vendor evaluations and partnerships across data, AI, and knowledge management to ensure the organization leverages the right capabilities and solutions to achieve its objectives.

Essential Requirements

• Bachelor's or Master's degree in Computer Science, Information Management, Data Science, AI, Analytics, Engineering, or a related field.
• 10+ years of experience in Data, Analytics, AI, Data Governance, Knowledge Management, or Digital Transformation.
• Experience with AWS Data Platforms, Data Lakehouse Architectures, Collibra, Knowledge Graphs, Vector Databases is esssential
• Proven experience leading enterprise-scale data and knowledge initiatives.
• Experience working with senior business stakeholders and global organizations.
• Strong understanding of enterprise data governance and semantic technologies.

Desirable requirements

Experience with AWS Data Lakes and Analytics Ecosystem, Microsoft Fabric, Enterprise Data Platforms, Data Products, Metadata Management, Semantic Layer Technologies, Ontology Engineering, Taxonomy Design, Enterprise Search, AI Knowledge Repositories, Agentic AI Architectures, API and Integration Frameworks

Experience and knowledge in People & Organization domain: Core HR & Workforce, Aministration, Workforce Planning, People Analytics, Talent & Skills Intelligence, Learning & Capability Development, Organizational Effectiveness, Rewards & Compensation, Employee Experience, Workforce Transformation

Experience and knowledge in Corporate Functions domain: Legal, Security & Information Security, Ethics, Risk & Compliance (ERC), Environmental, Social & Governance (ESG), Corporate Affairs, Internal Audit, Corporate Communications, Finance

Commitment to Diversity & Inclusion

We are committed to building an outstanding, inclusive work environment and diverse teams representative of the patients and communities we serve.

Why Novartis?

Skills Desired

Budget Management, Business Acumen, Digital Literacy, Influencing Skills, Operational Excellence (OpEx), Performance Management (PM), Project Management, Risk Management, Service Delivery Management, Strategic Planning, Technology Use