Group Data & AI Governance Manager

at  Bookingcom

At Booking.com, data drives our decisions. Technology is at our core. And innovation is everywhere. But our company is more than datasets, and lines of code. We’re the thrill of the first night in a new place, the excitement of the next morning, the friends you make, the journeys you take, the sights you see, and the food you sample. Through our products, partners and people, we can empower everyone to experience the world. We began by taking hotel bookings online over 20 years ago and we’ve been shaping the travel industry ever since. Today, we’re building a platform that connects all parts of the trip – from accommodation to transport, flights, tickets, tours and much more!

ROLE DESCRIPTION:

The Data & AI Senior Governance Manager is a senior thought-leader and team leader, responsible for the strategy and implementation of Data & AI Governance including metadata and master data management, data & AI quality and drive best practice across a broad range of Data & AI capabilities across the company.
Working with business and technology collaborators to define and implement a Data & AI Governance strategy that is clear, crisp and right sized for business objectives and compliance obligations across Booking.
Key to success in this role is the ability to translate an expert level of Data & AI Governance knowledge into communications and storytelling for executive sponsors and key stakeholders and deliver tangible benefits for the business.
This role demands skills as an evangelist, a partner and a people leader - at a time where transformation and modernization of our data ecosystem is an Org level priority.

KEY JOB RESPONSIBILITIES AND DUTIES:

• Leading Central Tech Data & AI Governance to define, review and update the policy and related Standards Bring clarity and engagement to the roll out of Data Ownership and Stewardship across the organization
• Partner with the Data & AI Governance Solution Architect in ensuring design principles are embedded for Data and AI Governance in design, and throughout the data & AI lifecycle in all strategic data & AI initiatives and programes.
• Collaborating with Risk and Compliance to understand Data Governance Risk position and appetite, to communicate, lead and measure mitigation activities and how Data & AI governance can support the implementation and compliance for data and AI across Booking
• Build, own and maintain data & AI asset cataloging and metadata management, covering data lineage, classification and definitions documentation
• Ensure the central Data & AI catalog is maintained, user friendly, clear and accessible for all consumers
• Collaborate with Data & AI Stewards to design new strategies, solutions and rules for data quality validation, to ensure data accuracy and reliability
• Collaborate with Data & AI Engineering Managers to develop strategies and standards for monitoring, failure detection, and data availability to ensure data and algorithm timeliness and completeness
• Lead proactive and reactive resolution of data & AI governance and compliance issues and incidents, reporting key KPIs to relevant stakeholders including the Data & AI Governance boards
• Ensure alignment between data & AI governance methodology, Data Privacy procedures and requirements, the IT Information Security strategy and any new regulatory compliance such as DMA/ DSA and EU AI Act by working closely with Legal teams.

ROLE QUALIFICATIONS AND REQUIREMENTS:

• Experience led understanding of downstream impact of Data & AI Governance processes and policy, experience in shaping these to balance compliance and pace
• Knowledge of industry Data Governance tooling, ideally including assessment, rollout and management experience
• Strong knowledge of Data Ownership and Stewardship structure, definition and onboarding
• Expert knowledge of implementing and leading Data & AI Governance Risk and issue assessment and strategy
• Strong knowledge of data & AI governance & protection frameworks, eg GDPR, DMA etc
• Expert knowledge of data quality requirement definition and implementation methodologies and tools
• Expert knowledge of Data Management requirements based on best practices, e.g. DAMA-DMBOK
• Working knowledge of Enterprise Architecture, e.g. TOGAF
• Working knowledge of database querying languages or scripting tools, e.g. SQL, VBA, Pandas, R
• Experience in leading teams, including managing managers.