Are you looking for an exciting opportunity to join a dynamic and growing team in a fast paced and challenging area? This is a unique opportunity for you to work in our team to partner with the Business to provide a comprehensive view.
As a Vice President, Data Governance in the Commercial & Investment Bank Chief Data Office, you play a senior delivery role in defining and implementing governance frameworks that strengthen data management, reduce risk, and improve transparency. You partner across teams to establish data ownership, define roles and responsibilities, and build operating models so that governance is practical and consistently applied. You translate complex topics into clear executive materials that support informed decisions and effective oversight, while supporting assurance, issue management, and remediation tracking to keep governance outcomes controlled, auditable, and future-ready. You also help embed responsible AI and automation into governance processes with appropriate human oversight, collaborating closely with business leaders and corporate partners to align priorities, manage dependencies, and deliver agreed outcomes. You will bring structure to ambiguous problems, apply sound risk-based judgment, and identify opportunities to simplify workflows, strengthen documentation, and improve reporting so stakeholders can act quickly and confidently
Job responsibilities
- Prepare executive-ready materials for governance forums, senior committees, audits, regulators, and client engagements
- Support implementation of Data Owner and In-Business Chief Data Officer role accountabilities and responsibilities
- Develop management information reporting, dashboards, scorecards, and training metrics to track performance and risk
- Maintain governance documentation, operating models, standards, and controls to support consistent execution
- Draft concise decision papers and presentations for senior stakeholders and external reviewers
- Partner with business leaders to contribute to data strategy, shape priorities, and maintain strong delivery discipline
- Coordinate assurance activities by identifying risks, developing remediation plans, and tracking issues through closure
- Promote responsible data use, data literacy, and controlled adoption of AI-enabled working practices through training and guidance
- Own project plans, milestones, dependencies, delivery risks, and stakeholder alignment for assigned cross-functional initiatives
Required qualifications, capabilities, and skills
- Demonstrate at least seven years of experience in financial services, financial technology, data governance, data risk, controls, or related disciplines
- Deliver complex cross-functional initiatives with clear ownership, sound judgment, and consistent follow-through
- Apply strong knowledge of data governance concepts including data ownership, data quality, lineage, metadata, control design, and issue management
- Influence senior stakeholders and build alignment across matrixed teams without relying on direct authority
- Communicate clearly in writing and verbally, translating complex data, risk, and technology topics into executive-level messaging
- Analyse data and trends to assess risk, identify root causes, and recommend pragmatic actions
- Practice responsible use of AI-enabled productivity tools including privacy, confidentiality, prompt discipline, and human-in-the-loop controls
- Improve governance workflows through automation and analytics while maintaining auditability and appropriate oversight
- Produce high-quality executive materials and reporting using PowerPoint, Excel, and visualisation or workflow tools
- Support effective project and change management including prioritization, dependency management, and timely escalation
- Model resilience, adaptability, attention to detail, and continuous learning in a rapidly evolving data and AI environment
Preferred qualifications, capabilities, and skills
- Experience delivering data governance or data risk initiatives within an investment bank or other highly regulated financial institution
- Understanding of banking and markets businesses, transaction flows, and front-to-back operating models
- Familiarity with data privacy, data localisation, records retention, and access management expectations
- Knowledge of AI governance, model risk, machine learning lifecycle controls, data ethics, and responsible innovation
- Exposure to data governance tooling such as data catalogues, lineage solutions, metadata management, data quality monitoring, workflow automation, or issue management platforms
- Proficiency with analytics and automation tools such as Tableau, Qlik, Alteryx, Python, or SQL
- Experience coaching teams on data literacy and controlled adoption of new technologies