Lead, Data & AI Governance

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.

Responsibilities:

Strategy, Framework & Policy Architecture

• Define Group-wide Data & AI Governance strategy, framework, operating model and roadmap, aligned to business strategy and AI ambitions
• Author and maintain the Group's policy architecture - policies, standards, guidelines and procedures
• Provide oversight, challenge and monitoring of adherence to policies and standards
• Lead the continuous-improvement agenda for governance maturity through targets and metrics

Governance Operating Model & Stewardship

• Establish the governance model: define decision rights (RACI), and Data Owners and Stewardship roles across the business units
• Translate governance topics into business-relevant insights for the relevant audiences.

Data Governance, Catalogue & Metadata Standards

• Set Group standards for data ownership, critical data elements, business glossary, metadata, data classification and dataset certification
• Mandate data contracts on critical datasets and lineage coverage, embedding governance checks into the delivery lifecycle
• Own the access governance standard and govern access to data, balancing innovation with appropriate controls

Data Quality Management

• Own the Group data quality policy and standard - quality dimensions, rule libraries, thresholds and SLAs
• Oversee the data quality operating loop, per-domain scorecards, remediation to SLA and owner-accountability reporting
• Set the dataset certification regime before business use

Data Protection, Sharing & Retention

• Partner with Cybersecurity and Data Protection Office to develop and maintain the data protection framework and policies
• Oversee data-sharing, retention and disposal practices across various stakeholders
• Collaborate with Legal, Privacy and Compliance to ensure data compliance across jurisdictions
• Manage and escalate data protection risks, tracking mitigations to closure

Master Data Management

• Serve as design authority for master data capability, to centralize and manage master and reference data efficiently
• Broker and secure ratification of master data design decisions across systems and stakeholders
• Drive change management, adoption, integration and scaling of the MDM platform across the organization

Regulatory Compliance, Risk & Assurance

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

Leadership, Reporting & Culture

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

Requirements:

• 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.