VP Data Transformation (Data Strategy & Governance | Banking AI Lab)

My client is looking for a VP Data Transformation to lead the strategic data agenda for a newly established AI Lab within a leading banking organisation. This is a senior leadership position focused on data strategy, governance, operating model and transformation, ensuring the organisation has the data foundations, standards and governance required to scale AI, analytics and digital products across the bank. The successful candidate will be a strategic data leader who can translate business and AI ambitions into a clear enterprise data strategy, while driving the governance, operating model and transformation programmes required to make that strategy real.

Responsibilities

Define and own the enterprise Data Strategy and Data Transformation roadmap, aligned to the bank's broader technology, digital and AI strategy; Establish the data governance framework, including ownership, accountability, data quality, lineage, metadata, standards and controls; Define and evolve the organisation's Data Operating Model, including roles, responsibilities, decision rights and ways of working; Establish strong Data Ownership and Data Stewardship across business and technology functions; Drive enterprise-wide improvements in data quality, accessibility, consistency and trust; Develop frameworks for data governance, data products, critical data elements and data domains; Partner with the AI Lab and technology leadership to ensure data strategy supports AI, GenAI, advanced analytics and machine learning at scale; Drive data transformation initiatives across business functions, breaking down data silos and enabling greater reuse of enterprise data; Define and implement data governance policies, standards and controls aligned with regulatory and risk requirements; Establish appropriate data quality and data governance KPIs, dashboards and executive reporting; Work closely with Risk, Compliance, Information Security, Technology and business leadership to ensure data is managed appropriately within a regulated banking environment; Lead and influence senior stakeholders across the organisation to drive adoption of new data standards and operating models; Assess and prioritise data transformation initiatives based on business value, AI readiness and strategic importance; Build and lead high-performing data strategy, governance and transformation teams

Requirements

15+ years' experience across Data Strategy, Data Transformation, Data Governance, Enterprise Data or a related senior data leadership function; Proven experience leading enterprise-scale data transformation programmes; Strong track record developing and implementing Data Strategy and Data Governance frameworks within complex organisations; Deep understanding of modern data architecture and platforms, sufficient to work credibly with Data Architects, Data Engineers and AI teams; Experience establishing or transforming data operating models, including data ownership, stewardship and governance structures; Strong understanding of data quality, metadata, lineage, master data and data management principles; Experience working with senior executives and influencing business and technology leadership; Strong commercial and strategic judgement, with the ability to connect data investment to business outcomes and measurable value

Nice to have

Experience within banking, financial services, fintech or another highly regulated environment is strongly preferred; Experience with regulatory data requirements and frameworks such as BCBS 239 would be highly advantageous; Exposure to AI / GenAI transformation and AI-ready data strategies is highly desirable; Successfully built and executed enterprise Data Strategies; Established governance and operating models; Driven measurable transformation across complex organisations; Comfortable operating at VP / C-suite level; Combines Data Strategy + Governance + Transformation + strong banking domain experience; Clear understanding of how high-quality, well-governed data enables AI and GenAI at enterprise scale