Lead, Data & AI Governance

About SATS

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, 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 215 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.

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Job Description

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. The role defines the Group-wide strategy, framework and policy architecture; provides oversight, challenge and monitoring of adherence while business domains execute the controls. The Lead partners closely with business, technology, risk, compliance, legal, privacy and cybersecurity stakeholders across SATS' global network to ensure data and AI assets are managed effectively, securely, ethically and in compliance with regulatory requirements.

The successful candidate will translate complex data and AI governance concepts into clear, business-relevant insights, embed governance into engineering delivery, and build a culture of data accountability and responsible AI.

Location:

Mumbai/Singapore

Key Responsibilities

-Strategy, Framework & Policy Architecture

· Define the Group-wide Data & AI Governance strategy, framework, operating model and multi-year roadmap across the four pillars, aligned to business strategy and AI ambitions.

· Author and maintain the Group's policy architecture - policies, standards, guidelines and procedures (e.g. data governance and ownership, data classification and handling, AI acceptable use and risk, data quality, master data, records and retention).

· Provide oversight, challenge and monitoring of adherence to policies and standards.

· Lead the continuous-improve

-Governance Operating Model & Stewardship

· Design the governance model: define decision rights (RACI), and appoint, develop and sponsor domain Data Owners and Data Stewards across the business units.

· Translate governance topics into clear, business-relevant insights for the relevant audiences, building confidence across teams.

-Data Governance, Catalogue & Metadata Standards

· Set the Group standards for data ownership, critical data elements, business glossary, metadata, data classification and dataset certification, and oversee their implementation in the enterprise data catalogue.

· Mandate data contracts on critical datasets and lineage coverage, embedding governance checks into the delivery lifecycle with platform engineering.

· 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 agreed with data owners.

· Oversee the data quality operating loop, per-domain scorecards, remediation to SLA and owner-accountability reporting.

· Set the dataset certification regime so critical datasets carry named…