Senior Data Governance Engineer (SG)

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 Senior Data Governance Engineer is a hands-on technical role that builds and runs capabilities across Data Governance, Master Data Management, and Data Quality. Working closely with the Data & AI team, the role turns the Group's policies and standards into working systems: an operated data catalogue, data quality rules executing in pipelines, and master data match/merge and golden records.

The successful candidate is an implementer and operator - an engineer who works hands-on, administers governance platforms, and automates the governance - partnering closely with business, technology, risk, legal, privacy and cybersecurity stakeholders.

Data & AI Governance Framework Implementation

• Implement the Group's Data & AI Governance policies and standards as working controls - checks, contracts and rulesets that execute in pipelines and the delivery lifecycle.
• Build and maintain supporting guidelines, patterns and playbooks for delivery teams.
• Automate policy attestation, exception tracking and control evidence, and monitor control effectiveness.

Data Catalogue, Metadata & Lineage

• Administer, configure and extend the enterprise data catalogue.
• Automate metadata capture across the data platform, and implement data contracts and data lineage.
• Maintain accurate data definitions, classifications and steward records at scale.

Data Quality Management

• Author, test and operate data quality rules embedded in pipelines, with thresholds and SLAs agreed with data owners under the Group data quality standard.
• Build and run per-domain data quality scorecards and monitoring.
• Enforce the dataset certification gate.

Master Data Management

• Build and operate the master data match/merge pipelines.
• Produce and maintain golden records on the MDM platform, published for consumption under data contracts.
• Run the steward exception queue with service levels and evidence, monitoring duplicate rates, match precision and golden-record coverage.

Access, Reporting & Enablement

• Execute periodic access recertification cycles, and implement retention, disposal and data-sharing controls.
• Build and maintain governance metrics, dashboards, and reporting.
• Deliver runbooks and hands-on support that enable Data Owners, Data Stewards and delivery teams to self-serve, fostering a culture of data accountability

Key Requirements

• Bachelor's degree in Information Management, Computer Science, Information Systems, Data/Analytics, Engineering or a related discipline.
• More than 6 years of hands-on experience across Data Governance, Data Quality, Master Data Management or data engineering with a governance focus.
• Strong SQL and working Python for profiling, rule development, tooling and automation; experience with entity-resolution / record-linkage and match/merge pipelines is a strong advantage.
• Hands-on administration of governance and data catalogue platforms such as DataHub, Microsoft Purview or similar.
• Production experience implementing data quality rules, monitoring, scorecards and remediation workflows embedded in data pipelines.
• Working knowledge of data contracts, data lineage and version-controlled, CI/CD-based delivery on a modern cloud data platform.
• Strong understanding of data management disciplines, including metadata, master data, data quality, data lineage, data stewardship and data privacy, and of applicable data regulatory and compliance requirements.
• Strong stakeholder coordination and communication skills across business and technology teams in a global or regulated environment.