Data & AI Governance Manager

The Data & AI Governance Manager joins Booking Holdings India COE in Bangalore to lead governance configuration and operations while contributing directly to cross-organizational initiatives. The role manages a small team of specialists and analysts, potentially including onshore and offshore contractors, and supports the company’s efforts to make data and AI assets secure, trusted and accessible.

Responsibilities

• Lead and coach a team of up to 5–7 people; set quarterly and annual objectives, estimate work, conduct performance reviews, improve team practices, support hiring and compensation decisions, and resolve communication or team conflicts.
• Apply data and AI governance policies, standards and processes. Clarify data ownership and stewardship responsibilities, support steward onboarding, and expand practices including data literacy, cataloging, profiling, classification, lineage, metadata and master data management.
• Integrate requirements from GDPR, DMA, SOx and the EU AI Act into governance frameworks and controls. Work with the wider governance team to improve compliance practices and identify, track and mitigate risks.
• Partner with governance specialists, Architecture, Product and Engineering on metadata configuration. Lead metadata design execution, testing, reporting and handover for complex agile initiatives. Serve as a point of contact for metadata inquiries and present updates to stakeholders, including VP-level leaders.
• Use Jira and Confluence to structure delivery workflows, track configuration changes and document work. Guide the team through technical and organizational change.

Requirements

• 5–8 years of relevant technical experience, including 3+ years focused on data governance or 5+ years in a broader data or analytical role. At least 1–2 years each in metadata management and managing, building and growing data teams are also specified.
• Strong SQL skills for metadata validation and integration troubleshooting; experience applying data-governance-as-code practices with Git and test, staging and production environments.
• Ability to configure asset types, domains, communities and relationships; design automated approval, issue-management and asset-onboarding workflows using tools such as BPMN 2.0, Java or Groovy; and design metamodels covering business glossaries, data catalogs and AI model registries. Understand tracking of model versions, training datasets, fairness metrics and accuracy scores.
• Strong written and spoken communication, stakeholder management and ability to work across technical and non-technical teams. A data governance certification, such as DAMA or DGI, is a plus, not a requirement.