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Job Description
ABOUT THE ROLE:
The Commercial Data Ecosystems & AI Readiness Lead is responsible for building and governing scalable trusted and AI-ready commercial data foundations across CEE GTM platforms and capabilities.
The role drives alignment of commercial data metadata governance and semantic standards across business units platforms and regions to enable analytics GenAI and future Agentic AI use cases.
Working across Commercial Enterprise Data & AI AI/D and platform teams the role ensures commercial data ecosystems are interoperable reusable governed and aligned with enterprise standards.
Key responsibilities include:
- Defining commercial data governance and AI-readiness standards
- Driving metadata lineage data quality and semantic consistency across platforms
- Enabling reusable and scalable commercial data products and services
- Supporting AI/GenAI use cases through trusted and contextualized data foundations
- Aligning commercial platforms business units and enterprise data capabilities
- Partnering with business and technology stakeholders to drive adoption and transformation
ACCOUNTABILITIES:
Enterprise Commercial Data Ecosystems & AI Readiness
- Define and operationalize the enterprise strategy for commercial data ecosystems semantic interoperability and AI-ready architectures across GTM platforms
- Establish scalable governance and operating models for commercial metadata ontology alignment lineage interoperability and reusable data assets
- Drive alignment between commercial business priorities enterprise data strategy and AI transformation initiatives
- Enable AI-ready data ecosystems supporting analytics GenAI RAG knowledge graph and Agentic AI capabilities
- Partner with enterprise data and AI organizations to ensure commercial data ecosystems align with enterprise AI security privacy and governance standards
Commercial Metadata Governance & Semantic Foundations
- Establish and govern enterprise-wide metadata standards business glossaries semantic definitions lineage frameworks and Critical Data Elements (CDEs)
- Define governance frameworks for:
- Business metadata
- Technical metadata
- Data quality
- Access controls
- Semantic consistency
- Lifecycle management
- Lead the adoption of ontology-aligned and semantically interoperable data structures across commercial domains
- Govern and approve changes to commercial data definitions lineage semantic structures and interoperability models across business units and geographies
- Ensure enterprise-critical commercial data assets are traceable to business processes decision-making analytics and AI consumption layers
AI & GenAI Data Enablement
- Enable trusted and contextualized data ecosystems supporting GenAI RAG intelligent search semantic reasoning and AI agent use cases
- Partner with AI and architecture teams toestablishAI-ready commercial data foundations and semantic enrichment capabilities
- Support the operationalization of reusable commercial knowledge assets semantic layers and contextual data services for AI-driven capabilities
- Ensure commercial data ecosystems areoptimizedfor future AI and Agentic AIscalability
StakeholderEngagement
- Act as a strategic advisor across commercial data AI and platform organizations on commercial data and AI-readiness initiatives
- Build andmaintaingovernance forums and communication channels across enterprise stakeholders
- Provide leadership visibility on progress risks priorities and transformation outcomes
- Influence enterprise adoption of standards and governance practices through strong business engagement storytelling and technical credibility
- Drive alignment between enterprise transformation priorities and commercial data ecosystem capabilities
EDUCATION BEHAVIOURAL COMPETENCIES AND SKILLS:(List the essential and desirable education and competency requirements to perform the primary responsibilities of the job.Anyminimumrequirements should benoted.)
Education
- Bachelors degree in Business Engineering Data/Digital or related field (advanced degree preferred)
Experience (1214 years)
- Experience in pharmaceutical life sciences healthcare or other regulated industries
- Strong understanding of commercial data domains and processes within pharma/life sciences environments preferred
- Experience supporting Commercial functions such as Customer Experience Patient Services Medical Digital Health Market Access or Content platforms preferred
- Proven experience in enterprise data strategy governance metadata management interoperability and AI-ready data ecosystems
- Experience with cloud and enterprise data platforms (AWS Databricks enterprise data platforms)
- Familiarity with AI/GenAI data requirements including RAG semantic search contextualized data and AI-driven use cases
- Exposure to ontology semantic layers knowledge graph and enterprise metadata management concepts preferred
- Proven ability to work across matrixed global organizations and influence senior business and technology stakeholders
Core Skills & Leadership Capabilities
- Strategic and enterprise-level thinking
- Strong analytical and data-driven decision-making capabilities
- Ability to translate complex technical concepts into business-relevant outcomes
- Strong stakeholder management and influencing capabilities
- Excellent communication and storytelling skills
- Strong cross-functional orchestration and governance leadership
- Self-driven with the ability to structure prioritize and deliver in complex enterprise environments
Locations
IND - Bengaluru
Worker Type
Employee
Worker Sub-Type
Regular
Time Type
Full time
Employment Type : Full-Time
Experience: years
Vacancy: 1
