New opportunity

SVP, Data & AI Governance Lead (UDO Office), Group Marketing & Communications

DBS Bank Ltd · Singapore

About this role

The Data & AI Governance Lead will drive the Data & AI Governance agenda across Group Marketing & Communications and its regional markets. This role provides leadership and oversight for data ownership, quality, metadata management, risk, and responsible AI practices. You will implement governance frameworks to improve trust, strengthen regulatory compliance, and enable responsible AI-driven innovation. Responsibilities: Define and drive the Data & AI Governance strategy, operating model, and roadmap. Establish ownership and stewardship for critical marketing and analytics data assets. Drive adoption of governance policies, standards, and tooling. Lead data quality improvement initiatives and resolve systemic data issues. Establish governance for metadata, business definitions, and lineage. Strengthen data and AI risk management through effective controls and remediation. Govern the responsible use of customer and marketing data, including oversight of AI and advanced analytics use cases. Partner with senior stakeholders across Marketing, Technology, and Compliance to drive outcomes. Lead regulatory and audit readiness activities. Requirements: 12+ years of experience in Data Governance, Data Management, Data Quality, Data Risk, or related disciplines. Proven experience leading marketing data governance or transformation initiatives. Experience working with senior business and technology stakeholders in complex organizations. Strong knowledge of data governance, quality, metadata, and control frameworks. Experience managing data across the marketing technology ecosystem (e.g., Adobe Analytics, Google Analytics, AppsFlyer). Knowledge of responsible AI, AI governance, and evolving regulatory requirements. Hands-on experience developing data products and mapping data flows. Experience with enterprise data governance platforms such as Collibra or OpenMetadata. Professional certifications in data management, governance, or risk are preferred. Experience within financial services or data-intensive industries is preferred.

For full details about this role, click “Apply on company site” to view the employer’s original posting.

Skills for this role

Data GovernanceData ManagementData QualityData RiskMarketing DataAnalyticsRegulatory ComplianceMetadata ManagementData LineageResponsible AIAI GovernanceAdobe AnalyticsGoogle AnalyticsAppsFlyerCollibraOpenMetadataStakeholder Management

Checking your profile…

Preparation suggestions, not the employer’s actual interview questions. Always check the original posting for current requirements.

Understand the role

What matters most

Define and Execute Data & AI Governance Strategy
The primary mandate is to establish a comprehensive operating model and roadmap for data and AI governance across Group Marketing & Communications. You must translate high-level governance frameworks into actionable policies, standards, and tooling adoption that improve data maturity and transparency across regional markets.
Strengthen Marketing Data Risk and Compliance
You are responsible for ensuring the responsible use of customer and marketing data, specifically overseeing AI and advanced analytics use cases. This requires implementing effective controls, monitoring risk, and ensuring audit readiness to meet evolving regulatory requirements in a financial services context.
Drive Cross-Functional Stakeholder Alignment
Success depends on partnering with senior leaders across Marketing, Technology, and Compliance. You must influence these stakeholders to adopt governance practices, resolve systemic data issues, and ensure that data ownership and stewardship are clearly defined for critical marketing assets.

Likely challenges to think through

Balancing Innovation with Strict Governance
The role requires enabling AI-driven innovation while simultaneously enforcing rigorous risk controls. Prepare to discuss how you have previously navigated this tension, specifically by building guardrails that facilitate speed-to-market without compromising regulatory compliance or data integrity.
Managing Complexity in the Marketing Technology Ecosystem
Marketing data is often fragmented across platforms like Adobe Analytics, Google Analytics, and AppsFlyer. You will face the challenge of mapping data flows and establishing lineage across these disparate systems. Prepare to demonstrate your technical familiarity with these tools and your approach to creating a 'single source of truth' in a complex enterprise environment.

Practice your answers

Technical practice

Designing a Data Governance Operating Model for Marketing

What to coverExplain how you would structure a governance operating model specifically for a complex marketing technology ecosystem. Focus on how you define roles, responsibilities, and decision-making rights between central governance teams and regional marketing units.

Managing Data Lineage in Marketing Tech Stacks

What to coverDescribe your approach to mapping data flows across platforms like Adobe Analytics, Google Analytics, and AppsFlyer. Discuss how you ensure metadata consistency and lineage transparency when data moves between these tools and internal customer data platforms.

Implementing Responsible AI Frameworks

What to coverHow do you operationalize responsible AI principles within a financial services marketing context? Address how you balance innovation with regulatory compliance, specifically regarding bias mitigation, transparency, and the ethical use of customer data in predictive models.

Data Quality Remediation Strategies

What to coverDescribe a methodology for identifying and resolving systemic data quality issues that impact marketing analytics and reporting. Suggest how you prioritize remediation efforts when dealing with cross-functional data silos.

Leveraging Governance Platforms for Compliance

What to coverDiscuss how you would utilize tools like Collibra or OpenMetadata to automate compliance and audit readiness. Focus on how these platforms support the documentation of critical data elements and business definitions.

Data Risk Management in Marketing

What to coverWhat are the primary data risks associated with modern marketing automation and audience management? Explain how you would design controls to monitor and mitigate these risks while maintaining marketing agility.

Developing Data Products for Marketing

What to coverExplain your process for developing data products that serve marketing use cases. Focus on how you ensure these products are governed, discoverable, and aligned with enterprise data standards.

Navigating Evolving AI Regulations

What to coverHow do you stay ahead of changing global data and AI regulations in a regional banking environment? Suggest a framework for translating these regulatory requirements into actionable policies for marketing teams.

Behavioural practice

Influencing Senior Stakeholders on Governance

What to coverDescribe a situation where you had to convince senior business leaders to prioritize data governance initiatives over immediate marketing delivery goals. Focus on how you articulated the long-term value of trust and compliance.

Driving Enterprise-Wide Change

What to coverProvide an example of a time you led a significant data transformation or governance adoption across a complex organization. Highlight the specific actions you took to overcome resistance and ensure cross-functional alignment.

Resolving Cross-Functional Conflicts

What to coverTell us about a time you had to mediate a dispute between Technology, Marketing, and Compliance teams regarding data usage or ownership. Explain how you reached a resolution that satisfied all parties while maintaining governance standards.

Managing Audit and Regulatory Readiness

What to coverDescribe your experience leading a team through a high-stakes audit or regulatory review. Detail how you prepared the organization and managed the remediation of any identified gaps.

Sharpen your knowledge

Topics to prepare

Responsible AI and Regulatory Frameworks
Review evolving AI governance standards and financial services regulations relevant to marketing data. Exercise: Draft a high-level compliance checklist for an AI-driven marketing campaign, ensuring alignment with data privacy and transparency requirements.
Marketing Data Governance Strategy
Understand the lifecycle of marketing data from collection to activation. Exercise: Design a conceptual operating model that defines data ownership and stewardship roles for a complex marketing technology ecosystem.

Skills to revise

Enterprise Governance Tooling
Familiarize yourself with the core functionalities of platforms like Collibra or OpenMetadata. Exercise: Map out how you would structure a metadata repository for a hypothetical customer data platform to ensure lineage and discoverability.
Data Flow Mapping and Product Development
Practice documenting data transformations and lineage for marketing use cases. Exercise: Create a visual data flow diagram for a cross-platform marketing campaign, identifying critical data elements and potential quality control points.
Stakeholder Management and Influence
Prepare to communicate complex governance requirements to non-technical senior leaders. Exercise: Develop a 5-minute executive summary pitch that justifies the ROI of a new data quality initiative in terms of marketing effectiveness and risk mitigation.

Your preparation checklist

Map your experience to marketing technology ecosystems
Prepare a summary of how you have governed data flows across platforms like Adobe Analytics, Google Analytics, and AppsFlyer. Be ready to explain how you ensured data quality and lineage within these specific marketing technology stacks.
Develop a framework for responsible AI in marketing
Draft a high-level approach for governing AI and advanced analytics use cases. Focus on how you would balance innovation with regulatory compliance and risk management, specifically within a financial services context.
Prepare a case study on stakeholder influence
Identify a past project where you drove enterprise-wide data governance change. Structure your narrative using the STAR method, highlighting how you influenced senior business and technology stakeholders to adopt new policies or tooling.
Formulate questions on the UDO Office mandate
Prepare thoughtful questions regarding the current maturity level of the UDO Office, the primary regulatory challenges facing the marketing department, and how the team currently balances regional market needs with group-wide governance standards.
Review enterprise governance platform implementation
Be prepared to discuss your hands-on experience with tools like Collibra or OpenMetadata. Focus on how you have used these platforms to manage metadata, business definitions, and data quality remediation in complex organizations.

Availability last checked: 18 Oct 2026. Status can change after a check; confirm on the employer’s website. Report an issue · Our checking policy

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