VP / Director, Data Governance Lead

SMBC Group

Fresher

Singapore

Posted 2 hours ago
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Job Description

Data Governance

Set the strategic direction and provide executive sponsorship for the enterprise-wide adoption and continuous enhancement of BCBS 239 principles, ensuring governance frameworks, risk management practices, and control environments support the Bank's regulatory and business objectives.
Establish and govern the enterprise Data Governance, Data Risk, Data Quality and Data Control operating model in partnership with the Enterprise Chief Data Office, ensuring consistent implementation of policies, standards, and accountability across the organization.
Define and oversee the multi-year Data Governance strategy and transformation roadmap, ensuring alignment with business priorities, regulatory expectations, investment decisions, and enterprise capabilities.
Provide leadership and oversight for Data Governance and Data Management functions, building organizational capability, developing future leaders, and fostering a culture of accountability, collaboration, and continuous improvement.
Serve as a trusted advisor to senior management and governance committees on data governance matters, influencing strategic decisions and promoting data as a critical enterprise asset.
Partner with executive stakeholders across business, technology, risk, compliance, and operations to drive enterprise-wide governance initiatives and embed data management considerations into strategic planning and business transformation programmes, including implementation and maintenance of data quality(DQ) rules, DQ systems, provision of data awareness and data culture programs etc.
Establish executive-level governance reporting and performance frameworks, ensuring appropriate oversight of governance maturity, regulatory compliance, data quality outcomes, risk exposure, and value realization.
Champion the strategic use of data and analytics to support business growth, operational excellence, client outcomes, risk management, and enterprise decision-making.
Provide effective challenge and oversight of data-related risks arising from business strategies, transformation programmes, and regulatory developments, ensuring appropriate governance, escalation, and remediation of material issues.
Drive alignment and consensus among senior stakeholders across regions and business functions, influencing strategic priorities and securing executive sponsorship for key data initiatives.
Oversee a portfolio of strategic Data Governance programmes, ensuring effective governance, disciplined execution, resource optimization, and delivery of measurable business and regulatory outcomes.

AI Governance

Define and champion the enterprise-wide AI Governance vision, strategy, and operating model, establishing governance principles, policies, standards, and oversight mechanisms to ensure the responsible, ethical, secure, and compliant adoption of Artificial Intelligence (AI), Machine Learning (ML), and Generative AI technologies across the organization.
Provide executive oversight and governance of AI risk management and model governance frameworks, ensuring robust lifecycle controls, validation standards, monitoring practices, explainability, accountability, bias management, and compliance with evolving regulatory and industry requirements.
Partner with senior business, technology, risk, compliance, legal, and data leaders to establish governance structures for the evaluation, approval, and ongoing oversight of AI initiatives, ensuring appropriate risk management, control effectiveness, and alignment with the Bank's strategic objectives.
Chair or sponsor AI Governance forums and decision-making bodies, providing effective challenge, oversight, and strategic direction on AI-related risks, opportunities, and investments.
Represent the organization on AI Governance matters with regulators, auditors, and executive management, ensuring alignment with regulatory expectations, industry best practices, and emerging AI governance requirements.
Establish executive-level AI Governance reporting and performance frameworks, monitoring AI adoption, compliance, risk exposure, model effectiveness, and business value realization while providing strategic insights and recommendations to senior leadership and governance committees.
Drive enterprise-wide awareness and adoption of responsible AI practices, fostering a culture of accountability, transparency, and ethical AI use across business and technology functions.