Summary
Lead the strategy, governance, innovation, adoption, and operations of Enterprise Data Products, AI-ready Data Foundations, Data Sharing, and Data & Analytics Platforms across Novartis. Drive the delivery of trusted, compliant, reusable, and interoperable data capabilities that accelerate Analytics, GenAI, Agentic AI, and digital transformation while maximizing business value. Partner across business, architecture, governance, engineering, security, and vendor ecosystems to scale enterprise data foundations and industrialize innovative platform capabilities, products, and accelerators.
About the Role
Major Accountabilities
- Define and execute enterprise data product, data sharing, and platform strategies aligned with Data Mesh, Lakehouse, AI, and enterprise architecture principles
- Lead platform innovation initiatives across Data, Analytics, Integration, GenAI, Agentic AI, Semantic Layer, Knowledge Graph, and automation technologies, driving incubation and industrialization of reusable capabilities.
- Establish AI-ready data foundations by enabling metadata management, data quality, lineage, observability, semantic context, and machine-readable data contracts.
- Drive enterprise data sharing and interoperability through data marketplaces, zero-copy sharing, federated access models, semantic standards, and governed data exchange architectures.
- Ensure governance, compliance, and risk management across data, analytics, integration, and AI platforms, embedding security, privacy, audit, and regulatory requirements into platform operations.
- Build strategic partnerships with business and technology stakeholders to align priorities, shape demand, guide roadmaps, and translate platform investments into measurable business outcomes.
- Drive adoption, evangelization, and value realization of enterprise data products and platform capabilities through stakeholder engagement, enablement programs, and performance measurement.
- Lead continuous improvement and vendor ecosystem management to enhance platform reliability, scalability, cost efficiency, operational excellence, and innovation outcomes.
Minimum Requirements
- Bachelor's degree in Computer Science, Engineering, Information Technology, Data Management, or a related discipline; advanced degree preferred.
- 15+ years of experience in Enterprise Data, Analytics, Integration Platforms, Data Products, Data Sharing, or Digital Platform environments.
- Proven experience in enterprise-scale solution architecture, platform transformation, product leadership, and technology innovation
- Strong expertise in Data Mesh, Data Lakes, Lakehouse architectures, Enterprise Data Products, and AI-ready data foundations