Lead, Data & AI Governance

About WhiteCrow

We are global talent research, insight, and sourcing specialists with offices in the UK, USA, Singapore, Malaysia, Hong Kong, Dubai, and India. Our international reach has helped us to understand and penetrate specialist markets at a global level. In addition to this, our service is also extended to complement our client's in-house talent acquisition teams.

About our client

Our client is a globally recognized organization headquartered in Southeast Asia, specializing in aviation support services, air cargo handling, ground operations, and institutional food solutions. The company provides a wide range of services, including passenger assistance, ramp and baggage handling, aviation security, aircraft cleaning, and laundry operations for the aviation sector.

Beyond aviation services, the organization operates large-scale central kitchens and food production facilities, catering to airlines, corporate clients, and institutions across diverse cuisines and service formats. With a strong presence across Asia-Pacific, Europe, the Americas, the Middle East, and Africa, the company supports global travel, trade, and logistics through an extensive international network, further strengthened by strategic acquisitions in recent years.

As a Lead, Data & AI Governance, you will be responsible for...

Strategy, Framework & Policy Architecture

• Defining the Group-wide Data & AI Governance strategy, framework, operating model, and roadmap, aligned with business strategy and AI ambitions.
• Authoring and maintaining the Group's policy architecture, including policies, standards, guidelines, and procedures.
• Providing oversight, challenge, and monitoring adherence to policies and standards.
• Leading the continuous-improvement agenda for governance maturity through targets and metrics.

Governance Operating Model & Stewardship

• Establishing the governance model, defining decision rights (RACI), and establishing Data Owner and Stewardship roles across business units.
• Translating governance topics into business-relevant insights for relevant audiences.

Data Governance, Catalogue & Metadata Standards

• Setting Group standards for data ownership, critical data elements, business glossary, metadata, data classification, and dataset certification.
• Mandating data contracts for critical datasets and lineage coverage, and embedding governance checks into the delivery lifecycle.
• Owning the access governance standard and governing access to data while balancing innovation with appropriate controls.

Data Quality Management

• Owning the Group data quality policy and standard, including quality dimensions, rule libraries, thresholds, and SLAs.
• Overseeing the data quality operating loop, domain-level scorecards, remediation against SLAs, and owner-accountability reporting.
• Setting the dataset certification regime before business use.

Data Protection, Sharing & Retention

• Partnering with Cybersecurity and the Data Protection Office to develop and maintain the data protection framework and policies.
• Overseeing data-sharing, retention, and disposal practices across various stakeholders.
• Collaborating with Legal, Privacy, and Compliance to ensure data compliance across jurisdictions.
• Managing and escalating data protection risks and tracking mitigations through to closure.

Master Data Management

• Serving as the design authority for master data capabilities, centralising and managing master and reference data efficiently.
• Brokering and securing ratification of master data design decisions across systems and stakeholders.
• Driving change management, adoption, integration, and scaling of the MDM platform across the organisation.

Regulatory Compliance, Risk & Assurance

• Conducting regulatory horizon scanning across jurisdictions where the company operates and re-baselining policies, controls, and plans as laws and standards evolve.
• Leading Group-wide Key Risk and Control Self-Assessment initiatives for Data and AI and coordinating data and AI audits, compliance reviews, and inspections.

Leadership, Reporting & Culture

• Owning governance KPI metrics, dashboards, and reporting for executive stakeholders.
• Serving as the senior liaison between business units and technology on governance requirements.
• Acting as an agent of change and inculcating a data and AI governance culture and discipline across the organisation.

What you already have...

• Bachelor's degree in Computer Science, Information Management, Data/Analytics, Engineering, Law, or a related discipline; a relevant postgraduate qualification is an advantage.
• Ongoing commitment to training and professional development.
• At least 8 years of working experience in data management, including 5 or more years leading Data Governance, Data Quality or Master Data Management programmes in multi-entity or regulated organisations.
• Extensive knowledge of data and AI regulatory, standards, and compliance requirements.
• Experience in AI or model governance, model risk management or responsible-AI programmes, including generative AI; exposure to agentic AI governance is an advantage.
• Proven track record standing up or transforming a governance function and operating model.
• Good understanding of risk management and compliance frameworks and related disciplines such as risk and control self-assessment.
• Experience in designing and delivering a Master Data Management capability.
• Strong hands-on technical fluency: proficient in SQL with working Python; credible with modern data catalogues (e.g. DataHub, Microsoft Purview), data quality frameworks, data contracts and lineage, policy-as-code access models and Git / pull-request-based delivery.
• Relevant certifications such as Certified Data Management Professional (CDMP), Certified Information Management Professional (CIMP) or Certified Information Systems Auditor (CISA) are strongly preferred.
• Excellent written and oral communication; skilled at authoring policies, standards, guidelines and executive materials that business and engineering teams can act on.