About Us

Headquartered in Singapore, SATS Ltd. is one of the world’s largest providers of air cargo handling services and Asia’s leading airline caterer. SATS Gateway Services provides airfreight and ground handling services including passenger services, ramp and baggage handling, aviation security services, aircraft cleaning and aviation laundry. SATS Food Solutions serves airlines and institutions, and operates central kitchens with large-scale food production and distribution capabilities for a wide range of cuisines.

SATS is present in the Asia-Pacific, the Americas, Europe, the Middle East and Africa, powering an interconnected world of trade, travel and taste. Following the acquisition of Worldwide Flight Services (WFS) in 2023, the combined SATS and WFS network operates over 225 stations in 27 countries. These cover trade routes responsible for more than 50% of global air cargo volume. SATS has been listed on the Singapore Exchange since May 2000. For more information, please visit www.sats.com.sg

Why Join Us

At SATS, people are our greatest asset and we build our success on the knowledge, expertise and performance of every contributor, by embracing diversity and uniqueness. As part of our holistic approach and commitment to embracing FAM (Fulfilling, Appreciated, Meaningful) in the workplace, we offer the runway to develop Fulfilling careers that foster your career growth, recognising and Appreciating the strength of talent and capabilities that we continue to build internally; and inspiring and encouraging each other to make Meaningful contributions in the work we do at SATS.

Key Responsibilities

The Lead, Data & AI Governance responsible for driving the enterprise Data & AI Governance function across four pillars - Data Governance, AI Governance, Master Data Management and Data Quality. This role is responsible for setting governance strategy, frameworks, policies, and oversight while partnering with business, technology, risk, compliance, legal, privacy, and cybersecurity teams across SATS' global network to ensure data and AI assets are managed effectively, securely, ethically and in compliance with regulatory requirements.

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 SATS 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

Key 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.