Data & AI Governance Lead

SGX Group; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

SGX Group is seeking a Data & AI Governance Lead to establish and mature enterprise governance for Data and AI, aligned with regulatory expectations. Collaboration with business, risk, legal, and compliance teams will be essential to embedding governance into daily operations and risk-aware innovation.

The role focuses on creating frameworks, policies, and operating models, driving governance maturity, and building a culture of trusted AI within SGX Group.

Qualifications

• 8–12 years of proven experience in Data Governance, AI Governance, or Enterprise Risk Management.
• Strong background in financial services or similarly highly regulated industries.
• Exceptional communication and influencing skills with C-suite executives, cross-functional leaders, and external regulators.

Responsibilities

• Establish governance frameworks and operating models for Data and AI.
• Lead the Enterprise Data & AI Council and drive cross-functional alignment.
• Develop enterprise data and AI policies and risk management procedures.
• Ensure regulatory alignment with MAS FEAT, MAS AI Governance guidance, PDPA, AI Verify, ISO/IEC 42001, and Model Risk requirements.
• Design and deliver data and AI awareness programs to promote governance culture.

Skills

Data Governance

AI Governance

Enterprise Risk Management

Communication with C-suite

Stakeholder Management

Job description

As the Data & AI Governance Lead, you will be the driving force behind establishing and maturing SGX’s enterprise Data and Artificial Intelligence governance capabilities. You will ensure that our data and AI models are managed as strategic enterprise assets, enabling trusted, secure, and compliant innovation.

Working collaboratively across business, technology, risk, legal, and compliance teams, you will develop the frameworks, policies, and operating models necessary to embed robust governance into our day-to-day operations. This is a highly visible role pivotal to establishing SGX as a leading, trusted, AI-enabled financial market infrastructure.

Key Responsibilities

Strategic Frameworks & Operating Model

• Establish the Governance Blueprint: Design and implement comprehensive Enterprise Data and AI Governance frameworks, operating models, and RACI matrices defining clear decision rights.
• Lead Governance Forums: Establish and drive the Enterprise Data & AI Council to ensure cross-functional alignment and executive visibility.
• Define Standards: Establish enterprise-wide data ownership, stewardship, accountability, and define critical data elements.
• Track Maturity: Define governance KPIs and establish regular reporting cadences for executive committees.

Policy, Lifecycle & Risk Management

• Policy Development: Develop and maintain the Enterprise Data, AI & Knowledge Policy, alongside detailed procedures for Data Quality, Metadata cataloguing, AI Safety, and the overall AI Lifecycle (in partnership with the CRO Function).
• AI Trust & Risk Assessment: Establish and maintain the Enterprise AI Inventory. Define AI classification schemas, conduct AI Trust Assessments, and champion Responsible AI implementation.
• Regulatory Alignment: Ensure all governance practices strictly align with internal policies and external standards, including MAS FEAT Principles, MAS AI Governance guidance, PDPA, AI Verify, ISO/IEC 42001, and Model Risk requirements. Support regulatory engagements as the domain expert.

Advocacy, Education & Culture

• Drive Adoption: Champion the adoption of data and AI governance best practices across all business units.
• Build Capability: Design and deliver Data & AI awareness programs, tailored governance training, and AI literacy initiatives to promote a deeply rooted culture of trusted AI at SGX.

What You Bring (Experience & Qualifications)

• Professional Experience: 8–12 years of proven experience in Data Governance, AI Governance, or Enterprise Risk Management.
• Industry Context: Strong background in financial services or similarly highly regulated, complex industries.
• Execution Track Record: Demonstrated success in designing and implementing enterprise-wide governance frameworks from the ground up.
• Domain Expertise: Deep understanding of AI governance, emerging global regulations, AI Risk, Model Risk, Metadata management, and Data Quality principles. (Familiarity with Enterprise Architecture is a plus).
• Stakeholder Management: Exceptional communication and influencing skills, with a track record of effectively engaging C-suite executives, cross-functional leaders, and external regulators.

What Success Looks Like (Key Measures)

• Successful rollout and operationalization of the Enterprise Data and AI Governance Frameworks and the Enterprise AI Inventory.
• The Data & AI Council is established, active, and driving measurable outcomes.
• Enterprise policies are approved, adopted, and seamlessly integrated into business processes.
• AI Trust Assessments are standardized and embedded into the technology lifecycle.
• Demonstration of increased enterprise governance maturity and positive regulatory outcomes.