VP, Data Governance Lead

Headquartered in Tokyo, Sumitomo Mitsui Banking Corporation (SMBC) is a leading global financial institution and a core member of Sumitomo Mitsui Financial Group (SMBC Group). Built upon our rich Japanese heritage since 1876, we put our customers first and provide seamless access to, from and within the Asia Pacific region. SMBC is one of the largest Japanese banks by assets and maintain strong credit ratings across our global integrated network. We work closely as one SMBC Group to offer personal, corporate and investment banking services to meet the needs of our customers.

With sustainability embedded within our strategy and operations, we are committed to creating a society in which today’s generation can enjoy economic prosperity and well-being, and pass it on to future generations.

Data Governance

• Lead the enterprise-wide implementation and ongoing maturity of BCBS 239 principles by establishing governance frameworks, adoption roadmaps, compliance metrics, and sustainable control mechanisms across all business lines.

• Define, implement, and continuously enhance Data Governance, Data Risk, and Data Control standards in partnership with the Enterprise Chief Data Office, ensuring policies are consistently embedded into business operations.

• Develop and execute the strategic roadmap for Data Governance initiatives, maintaining oversight of a structured portfolio of work, delivery milestones, prioritization, resource allocation, and successful programme execution.

• Build, lead, and develop high-performing teams of Data Governance and Data Management professionals, fostering accountability, collaboration, and continuous capability development.

• Act as the senior subject matter expert for enterprise data governance, providing strategic guidance across major transformation programmes and ensuring alignment with regulatory expectations and organizational objectives.

• Partner with business, technology, risk, and compliance stakeholders to translate complex business requirements into practical data governance solutions that strengthen risk management, regulatory compliance, and operational effectiveness.

• Drive and manage data quality issue resolution across SMBC.

• Establish and monitor key performance indicators (KPIs) and governance metrics to measure programme effectiveness, regulatory compliance, data quality improvements, and overall business outcomes, providing regular updates to executive leadership and governance committees.

• Leverage data analytics to generate actionable business insights that support strategic decision-making, including growth initiatives, client origination, cross-selling opportunities, resource optimization, and operational efficiency.

• Assess and advise on data-related risks arising from strategic business decisions, ensuring adherence to regulatory obligations, ethical standards, and appropriate governance practices while escalating material issues where necessary.

• Drive stakeholder engagement across multiple business functions, building alignment, influencing senior executives, and achieving consensus on strategic data initiatives and governance priorities.

• Balance competing priorities across multiple concurrent programmes while maintaining focus on strategic objectives, execution excellence, and timely delivery of measurable outcomes.

AI Governance

• Establish and lead the enterprise-wide AI Governance framework, defining policies, standards, controls, and operating procedures to ensure the responsible, ethical, secure, and compliant use of AI, Machine Learning (ML), and Generative AI technologies across the organization.

• Lead the review of AI risk management and model governance practices, including model lifecycle management, validation, monitoring, explainability, accountability, bias assessment, and compliance with applicable regulatory and internal requirements.

• Partner with business, technology, risk, compliance, legal, and data stakeholders to evaluate, approve, and govern AI use cases, ensuring appropriate oversight, controls, and risk mitigation measures are embedded throughout the AI lifecycle.

• Establish AI governance metrics, reporting, and monitoring mechanisms to track AI adoption, performance, compliance, emerging risks, and business value realization, providing regular updates and strategic recommendations to senior management and governance committees.

Key Qualifications

• 8-10 years of progressive experience in Data Governance, Data Management, Data Risk, or Process Engineering within the banking or financial services industry, including significant leadership experience.

• Demonstrated expertise in BCBS 239 regulatory requirements, with a proven track record of leading large-scale implementation and transformation programmes within complex financial institutions.

• Strong knowledge of Data Governance frameworks, Data Operating Models, Data Risk Management, and regulatory compliance practices applicable to global financial services organizations.

• Proven experience leading multidisciplinary teams across multiple workstreams, driving execution excellence, talent development, and accountability for delivery.

• Excellent business analysis and problem-solving capabilities, with the ability to convert complex business and regulatory requirements into scalable governance solutions.

• Exceptional executive communication and stakeholder management skills, with the ability to influence senior leadership, negotiate priorities, and build consensus across diverse stakeholders.

• Strong analytical mindset with experience applying data-driven insights to support strategic business decisions and organizational transformation.

• Demonstrated ability to manage competing priorities in a fast-paced environment while maintaining attention to detail and delivering against strategic objectives.

• High level of integrity, sound judgment, and commitment to regulatory compliance, governance excellence, and continuous improvement