What does a chief data officer do?
A chief data officer (CDO) is the senior executive accountable for how an organisation collects, manages, protects and uses data.
Many organisations also give the role charge of artificial intelligence (AI), so the title may read chief data and AI officer.
The role sits on the executive team. A CDO often reports to the chief executive officer, the chief operating officer or the chief information officer. Large banks, insurers, public sector agencies and consumer firms in Singapore often have one.
You work with business heads, the chief information officer, legal, risk and compliance, and the data protection officer. You also lead data engineers, architects and analysts, and deal with regulators and technology vendors.
What the work involves
- Agree data and AI priorities with business heads and tie them to the organisation's goals.
- Chair the data governance council and settle disputes over data ownership, definitions and access.
- Review progress on data platform, analytics and AI projects against the business targets set for them.
- Check that data use follows privacy law, internal policy and the organisation's AI governance rules.
- Hire and coach data leaders, and plan who takes over key roles in the data and AI teams.
- Brief the board and senior leaders on data risks, value delivered and funding needs.
Pay in Singapore
The median is S$17,812 a month, gross.
Closest MOM occupation: Chief information officer/Chief technology officer/Chief information security officer (SSOC 13301). MOM, Occupational Wages 2025, Table 4 (all industries), June 2025. Full-time resident employees; gross monthly wage, excluding bonuses. Full pay data
Skills a chief data officer needs
Core skills
- Data architecture
- Data governance
- People management
- Stakeholder management
Tools and platforms
- Cloud data warehouses (BigQuery, Snowflake)
AI
- AI governance & risk
- AI literacy
Chief data officer job description
We are looking for a chief data officer to set and run our data and AI strategy.
You will own data governance, quality and access across the organisation. You will guide our move to cloud data platforms and lead a team of data and AI professionals. You will report to a C-suite leader and work closely with business heads, risk, legal and technology.
Responsibilities
- Set the data and AI strategy and align it with the organisation's vision and business plans.
- Set up and run the data governance framework, including data ownership, quality standards and shared definitions.
- Oversee data architecture and platform choices, including cloud data warehouses.
- Make sure data use follows the Personal Data Protection Act (PDPA), sector rules and internal policy.
- Put AI governance in place, including risk reviews, ethics checks and alignment with Singapore's Model AI Governance Framework.
- Define measures for the value of data and AI initiatives and report results to the executive team.
- Win support from senior leaders for data and AI programmes through a clear stakeholder plan.
- Hire, develop and retain data and AI talent, and plan succession for key leadership roles.
- Oversee how the organisation protects intellectual property tied to AI models and solutions.
- Track new data and AI tools and decide which ones the organisation should adopt.
Requirements
- A degree in computer science, information systems, statistics, engineering, business or a related field. A postgraduate degree is often preferred.
- Typically 12 to 20 years of experience in data, analytics or technology, with several years leading large teams.
- A record of running data governance, data architecture and analytics programmes across a whole organisation.
- Working knowledge of cloud data platforms such as Snowflake and BigQuery, and of AI and machine learning concepts.
- Good understanding of the PDPA and, in regulated sectors, the rules of the Monetary Authority of Singapore (MAS) or the sector regulator.
- Clear communication with boards, senior leaders and technical teams.
Chief data officer career path
Most chief data officers in Singapore start in analytics, data engineering, architecture or governance.
They then move into management and take on wider accountability for data across the organisation.
Data analyst
Entry
You prepare and analyse data to answer business questions and learn how data is produced and used.
Data governance specialist
Mid
You set data standards, manage data quality issues and work with data owners on policy and privacy rules.
Data governance manager
Senior
You lead a governance or architecture team, run the data council and report data risks to senior leaders.
Head of data
Lead
You run the whole data function, own the platform and analytics plans, and manage a budget and several teams.
Chief data officer / chief AI officer
Head · SkillsFuture title
You set data and AI strategy at executive level and answer to the CEO and the board for data value and risk.
Steps marked "SkillsFuture title" follow the career pathway in the SkillsFuture Skills Framework. The others are titles commonly used in Singapore.
Related jobs and their pay
| Related job | Median pay a month | Why it is related |
|---|---|---|
| Data architect | S$10,500 | You can return to hands-on design of enterprise data models and platforms if you prefer technical depth to people management. |
| Data governance specialist | S$8,471 | Your policy, quality and privacy experience carries over to specialist governance roles in regulated firms. |
| Risk analytics analyst | S$9,500 | A CDO's grasp of data risk and AI controls suits risk teams in banks and insurers. |
MOM Occupational Wages 2025, gross monthly wage, full-time resident employees. Each figure links to its salary guide.
Chief data officer interview questions
We wrote these questions from the skills this job needs. They are not an official question bank.
How would you build a data strategy for an organisation whose data sits in many separate business units?
What a good answer covers
- Starts from business goals and the decisions data should support
- Takes stock of data assets, owners and current quality
- Describes a target architecture and the order of work, with quick wins early
- Names measures such as adoption, data quality and business value
How would you set up a data governance programme from scratch?
What a good answer covers
- Defines an operating model with a council, data owners and data stewards
- Starts with a few critical data domains instead of everything
- Sets policies, quality rules and a data catalogue
- Creates a route to escalate disputes and track issues
- Links governance to business benefits so units want to take part
When would you choose a cloud data warehouse such as Snowflake or BigQuery over an on-premise one?
What a good answer covers
- Compares scaling needs, workload mix and cost control
- Covers security controls, access rules and data residency
- Considers staff skills and the cost of moving data
- Raises vendor lock-in and an exit plan
How do you decide between a central data platform, a federated model and a data mesh?
What a good answer covers
- Ties the choice to organisation size, structure and data maturity
- Explains who owns data and who owns the platform in each model
- Names the trade-offs in speed, consistency and duplicated effort
- Describes how common standards would still be enforced
How do you control access to sensitive data in a cloud data warehouse?
What a good answer covers
- Uses role-based access and the least-privilege principle
- Applies masking or tokenisation for personal and sensitive fields
- Encrypts data and keeps audit logs of who accessed what
- Reviews access regularly and removes it when roles change
What checks would you require before an AI model goes into production?
What a good answer covers
- Rates the risk of the use case and sets approval levels to match
- Tests for bias, accuracy and explainability
- Reviews training data sources, lineage and permission to use them
- Sets human oversight, monitoring for drift and a way to switch the model off
- Keeps an audit trail that follows Singapore's Model AI Governance Framework
How would you explain the risks of generative AI tools to your board?
What a good answer covers
- Uses everyday language instead of technical terms
- Covers wrong answers, leaks of confidential data and intellectual property exposure
- Proposes an approved tool list, a usage policy and staff training
- Balances risk with practical uses that bring business value
How do you measure whether data and AI programmes are paying off?
What a good answer covers
- Sets a baseline and links each project to a business outcome
- Tracks adoption, data quality and time saved as well as revenue or cost effects
- Reviews the portfolio regularly and stops projects that miss targets
- Reports in terms the finance team accepts
Sales and finance each report a different customer count, and the board has noticed. What do you do?
What a good answer covers
- Finds how each team defines a customer and where the data comes from
- Brings both teams together to agree one definition and one source of truth
- Names an owner for the metric and records it in the catalogue
- Fixes the issue in the shared data layer instead of in reports
- Keeps the discussion on the data, not on who is at fault
The CEO wants a customer-facing generative AI chatbot live in a few months. Risk and legal object over customer data. How do you proceed?
What a good answer covers
- Clarifies the business goal and the minimum useful version
- Runs a risk review on data used, outputs and customer impact
- Proposes a limited pilot with guardrails and human fallback
- Sets clear conditions for wider release and tells the CEO what the delay buys
A vendor tells you that a file with customer records may have been exposed. What do you do in the first day or two?
What a good answer covers
- Contains the incident and brings in security, legal and the data protection officer
- Establishes what data and how many people are affected
- Assesses whether the breach must be reported to the Personal Data Protection Commission and to affected individuals
- Records decisions and timings, then reviews the vendor controls afterwards
Your budget is cut sharply mid-year. Which data and AI work do you protect, and which do you stop?
What a good answer covers
- Ranks work by business value, risk and legal obligations
- Protects governance, security and compliance work that cannot be paused
- Pauses projects with unclear returns and says why
- Talks to affected business heads before announcing changes
Tell us about a time you built or rebuilt a data team. What did you change?
What a good answer covers
- Describes the team's starting point and the gaps found
- Explains hiring, role design and training choices
- Shows how the team kept its best people
- Gives a result the business noticed
Describe a time a senior leader refused to share their data or back a data initiative. How did you win them over?
What a good answer covers
- Finds out what the leader was worried about
- Offers a concrete benefit or a small pilot
- Gets a sponsor or evidence that carries weight
- Keeps the relationship intact afterwards
A team wants to reuse customer data collected for service delivery to build a new analytics model. How does the PDPA affect this?
What a good answer covers
- Checks the purposes the customer was told about and agreed to
- Considers whether consent, deemed consent or an exception applies
- Looks at anonymising or limiting the data used
- Works with the data protection officer and records the decision
- Sets how long the data is kept
Common questions about a chief data officer job
What does a chief data officer do?
A chief data officer sets the data and AI strategy and is accountable for data quality, access and governance. The CDO also leads the data teams and makes sure data use follows privacy law and company policy.
Is a chief data officer the same as a chief information officer?
No. A chief information officer runs the organisation's technology systems, while a chief data officer is accountable for how data is governed and used. In some organisations one executive covers both.
How many years of experience do you need to become a chief data officer?
Most chief data officers have around 12 to 20 years of experience. That usually includes time in data or technology roles and several years managing teams and budgets.
Does the chief data officer have to be the data protection officer?
No. The PDPA requires an organisation to appoint at least one data protection officer, who can be another person. A CDO often oversees or works closely with that officer.