Manager / Senior Manager (Data Governance & Management)

Gambling Regulatory Authority, Singapore; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

Gambling Regulatory Authority Singapore seeks a Manager / Senior Manager (Data Governance & Management) to lead data assets, ensuring IM8 compliance and supporting data-driven policy work.

You will establish governance policies, manage data quality and security, enable secure data sharing across agencies, and build governance capability including training and dashboards, with a focus on AI governance and responsible data practices.

Qualifications

• Background in Infocomm Technology or Computer Science or Electrical Engineering.
• At least 3 years of working experience in data governance, data warehouse management, data platform management and data analytic project management using PowerBI and Tableau.
• Strong foundation in data architecture, data platform, data quality management and database technologies.

Responsibilities

• Establish Data Governance Policies and Accountability.
• Assign clear roles such as Data Owners, Data Stewards and Custodians.
• Ensure accountability for data across business units.
• Develop roadmaps for data platform and pipelines that ensure availability, scalability, security and performance.

Skills

Data governance

Data quality

PowerBI

Tableau

Cloud platforms

Communication

AI governance

Education

Infocomm Tech / CS / E&E

Tools

PowerBI

Tableau

Job description

As Manager / Senior Manager (Data Governance & Management), you will manage GRA’s data assets to support the data needs, and compliance to the IM8 requirements.

Responsibilities

1. Establish Data Governance Policies and Accountability

• Define and maintain data governance policies, standards and procedures.
• Assign clear roles such as Data Owners, Data Stewards and Custodians.
• Ensure accountability for data across business units.
• Develop GRA’s roadmaps for data platform and pipelines that ensure availability, scalability, security and performance

2. Ensure Data Quality and Integrity

• Implement data quality frameworks, metrics, and monitoring.
• Drive remediation of data quality issues and root causes.
• Ensure data is accurate, complete, consistent, and fit for operational and decision-making purposes

3. Manage Data Risk, Security, and Compliance

• Ensure compliance with regulatory and Whole of Government requirements e.g. IM8, PDPA.
• Oversee data classification, access controls, retention and protection measures.
• Reduce risks relating to privacy breaches, unauthorized access and inappropriate use of data.

4. Enable Data Sharing and Business Value

• Promote trusted, secure, and efficient sharing of data across departments and agencies.
• Establish data dictionary, catalogues, metadata management and authoritative data sources.
• Support analytics, digital services, AI initiatives, policy development and operational decision-making through trusted data.

5. Build Governance Culture and Capability

• Develop organisational awareness and data literacy.
• Establish governance committees, reporting structures and performance dashboards.
• Train stakeholders on governance responsibilities and foster a culture where data is treated as a strategic asset.

6. Strengthen Data Integration with AI Capability

• Implement AI and ML strategies aligned with organisational objectives.
• Design and oversee end-to-end machine learning lifecycle processes.
• Establish model governance, monitoring, explainability, fairness,and risk management controls.
• Ensure compliance with Responsible AI, AI governance, security, privacy, and ethical guidelines.

Requirements

• Background in Infocomm Technology or Computer Science or Electrical Engineering
• At least 3 years of working experience in data governance, data warehouse management, data platform management and data analytic project management using PowerBI and Tableau
• Strong foundation in data architecture, data platform, data quality management and database technologies
• Preferably with experience in handling ETL/ELT tools and pipeline orchestration.
• Knowledge of cloud platforms (Azure, AWS, GCC, GDC, etc.).
• Good verbal and written communication skills
• Good interpersonal skills
• Good to have some experience with machine learning techniques, data regression, clustering, forecasting, RAG and anomaly detection.