Head of Enterprise Business Data Governance

Job Description Summary

This role is a critical enterprise leadership position responsible for building, institutionalizing, and continuously improving a robust, business‑led data governance capability across Sandoz, covering master data, reference data, transactional data, analytical data, and AI‑relevant datasets. The role ensures that data governance is embedded as a core enterprise governance capability and integrated into business‑as‑usual processes, providing consistent standards, clear decision rights, measurable adoption, and scalable execution across all business domains. The position is initially hosted under Technology with defined milestones, readiness criteria, and a structured transition to Business ownership, supporting long‑term sustainability and accountability.

Job Description Head of Enterprise Business Data Governance

Sandoz continues to go through an exciting and transformative period as a global leader and pioneering provider of sustainable Biosimilar and Generic medicines. As we continue down this new and ambitious path, unique opportunities will present themselves, both professionally and personally. Join us, the future is ours to shape

Job Summary

This role is a critical enterprise leadership position responsible for building, institutionalizing, and continuously improving a robust, business‑led data governance capability across Sandoz, covering master data, reference data, transactional data, analytical data, and AI‑relevant datasets. The role ensures that data governance is embedded as a core enterprise governance capability and integrated into business‑as‑usual processes, providing consistent standards, clear decision rights, measurable adoption, and scalable execution across all business domains. The position is initially hosted under Technology with defined milestones, readiness criteria, and a structured transition to Business ownership, supporting long‑term sustainability and accountability.

Your Key Responsibilities

Your responsibilities include, but are not limited to:

• Enterprise Data Governance Leadership
  • Define and own the Enterprise Business Data Governance strategy across master data, reference data, transactional data, analytical data, and AI‑relevant datasets, aligned with regulatory requirements, Company priorities, transformation initiatives, and AI readiness
  • Establish Data Governance as an enterprise‑wide capability embedded into business‑as‑usual processes, decision forums, transformation initiatives, and operational routines rather than as a separate project or overlay
  • Act as the single point of accountability for enterprise data governance frameworks, standards, governance forums, decision‑making, and escalation, while ensuring business domains retain accountability for data quality, remediation, and outcomes
• Governance Framework & Policy Ownership
  • Develop, maintain, and enforce the enterprise data governance framework, including policies, standards, definitions, and decision rights
  • Define clear ownership boundaries and interfaces with Data Privacy, Information Security, Risk, Compliance, and Enterprise Architecture, ensuring governance responsibilities are complementary and not duplicative
  • Establish and operate governance councils, stewardship forums, and escalation mechanisms to support enterprise decision‑making, adoption, and sustainable business ownership
• Operating Model & Capability Enablement
  • Design, implement, and operate a federated Hub-and-Spoke data governance operating model that balances central standards with business domain accountability and execution
  • Lead the Enterprise Data Governance Hub, including:
    • Governance cadence and forums
    • Metadata management, business glossary, and lineage standards Prepared by x / Review by x Date of issue: x
    • Data quality governance framework, domain‑level monitoring, remediation tracking, and continuous improvement
    • Metadata, data catalogue, lineage, provenance, retention, access, policy, risk, and compliance controls supporting analytics and responsible AI requirements Ensure governance execution capabilities remain embedded within business domains, with clear ownership for data quality and outcomes Drive change management, communications, training, and stewardship enablement to build data governance capability and adoption across business units
• Data Quality, Risk & Performance Management
  • Identify, assess, and mitigate enterprise data risks impacting regulatory compliance, operational performance, analytics, data traceability, provenance, and AI use cases Define, track, and report measurable KPIs, including percentage of domains with appointed data owners, data quality improvements, governance adoption, remediation timelines, stewardship coverage, and maturity progression across domains