Data Transformation Lead

Salt; Abu Dhabi; On-site; AED 600,000 - 1,000,000; Full time

Job summary

Salt seeks a VP Data Transformation to lead the strategic data agenda for our AI-enabled lab. The role focuses on data strategy, governance, operating model and transformation to scale AI, analytics and digital products within a regulated banking context.

You will translate business and AI ambitions into a clear enterprise data strategy, driving governance, operating model and transformation programmes to realise that strategy at scale.

Qualifications

• Experience developing enterprise data strategies and governance frameworks in complex organisations.
• Strong understanding of modern data architecture and data platforms.
• Proven ability to establish or transform data operating models including ownership and stewardship.
• Experience working with senior executives to translate business needs into data programs.

Responsibilities

• Define and own the Data Strategy and Data Transformation roadmap.
• Establish data governance framework, ownership, quality, lineage, metadata and controls.
• Define and evolve the Data Operating Model with clear roles and decision rights.
• Lead Data Ownership and Data Stewardship across business and tech.

Skills

Data Strategy

Data Transformation

Data Governance

Enterprise Data

Data Architecture

Regulatory Compliance

Job description

VP Data Transformation – Data Strategy & Governance | Fintech AI Lab

Location: Abu Dhbai

My client is looking for a VP Data Transformation to lead the strategic data agenda for a newly established AI Lab.

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.

Key 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.

Core Focus Areas

• Enterprise Data Strategy
• Data transformation roadmap
• Data maturity assessment
• AI / GenAI data readiness

Data Governance

• Data ownership and stewardship
• Metadata and lineage
• Data classification
• Governance frameworks and controls
• Data policies and standards

Operating Model

• Enterprise data operating model
• Data governance councils
• Business / Technology alignment
• Data accountability and decision rights
• Change management and adoption

Ideal Candidate

• 15+ years' experience across Data Strategy, Data Transformation, Data Governance, Enterprise Data or a related senior data leadership function.
• 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.
• 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.

What Will Differentiate You

My client is looking for a strategic data transformation leader, rather than a traditional Data Governance Manager or purely technical Data Architect.

The strongest candidates will have successfully built and executed enterprise Data Strategies, established governance and operating models, and driven measurable transformation across complex organisations.

You should be comfortable operating at VP / C-suite level, influencing senior stakeholders while still understanding the underlying architecture, technology and data challenges well enough to challenge technical teams and make informed strategic decisions.

The ideal profile combines Data Strategy + Governance + Transformation + strong banking domain experience, with a clear understanding of how high-quality, well-governed data enables AI and GenAI at enterprise scale.