Asia Wealth Management - Data Governance, Change The Bank, Director/ VP, Hong Kong

优缺点分析

角色解读

• Could progress to a wider Data Management or Chief Data Office leadership role across the firm's Asia wealth franchise.
• Exposure to cloud and agentic enablement pillars positions you for roles bridging governance with AI adoption.
• Potential lateral moves into Risk, Compliance, or Regulatory Reporting leadership in global banking.
• Lead the operational execution of the data governance framework across Private Wealth Management, ensuring data remains trusted and compliant.
• Chair and organize quarterly Data Governance Committee meetings, prepare materials, track actions, and update senior management.
• Maintain the data landscape inventory, coordinate metadata and data catalog initiatives, and oversee data quality issue remediation with business and technology stakeholders.
• Partner with Risk, Compliance, Legal, and Audit teams to gather evidence and respond to regulatory and audit requirements.
• Strong knowledge of data governance frameworks, data ownership models, and data lineage/metadata concepts.
• Proven project and stakeholder management ability, capable of driving adoption and remediation across cross-functional teams.
• Excellent communication and presentation skills to influence senior executives and run governance forums.
• Familiarity with financial services regulatory expectations and tools like Collibra, Power BI, or Snowflake.

申请策略

• Research Morgan Stanley's PWM business and its data strategy, particularly cloud and agentic enablement initiatives.
• Tailor your CV to demonstrate both data governance depth and ability to operate across business and technology.
• Emphasize 10+ years leading data governance, data quality, or regulatory reporting initiatives in financial services.
• Highlight examples of running governance committees, steering groups, or remediation programs with measurable outcomes.
• Demonstrate familiarity with data lineage, metadata, data catalog, and controls
• mention tools like Collibra, Power BI, Snowflake.
• Showcase senior stakeholder management and presentation skills with concrete stories.
• If not already fluent, deepen knowledge of data governance frameworks (e.g., DAMA-DMBOK) and regulatory expectations (e.g., MAS, HKMA).

面试指南

• Use structured STAR responses linking your experience to measurable outcomes, focusing on coordination, challenges, and actions.
• For governance design questions, propose a clear operating model covering ownership, forums, metrics, and escalation.
• Emphasize stakeholder influence by describing communication, alignment, and persistence strategies.
• How would you design and implement a data governance framework for a private wealth management business?
• Tell us about a time you led a data quality remediation program with multiple stakeholders.
• How do you influence senior stakeholders who resist data governance processes?
• How would you ensure data governance aligns with regulatory expectations such as HKMA or MAS?
• What experience do you have with metadata management, data lineage, and data catalog tools?