Head of Audit Data Governance

Summary of role purpose:
Audit Technology is delivering a significant transformation agenda to modernise how data is created, governed, used and shared across the UK Audit business.

As data becomes a foundational asset enabling Generative AI, digital audit delivery, and a more connected and efficient operating model we are expanding our leadership capability to ensure data is managed consistently, responsibly and strategically across all Audit portfolios.

The Head of Audit Data Governance will sit horizontally across our Solutions and Run & Maintain organisations, working closely with Product, Engineering, Architecture, Transformation, Operations, and the Audit Practice.

You will lead a multi‑pillar data function spanning Data Governance, Data Quality, Data as Insight, and Data as a Service , ensuring that data drives value, supports Audit Quality, and enables scalable and trustworthy digital products.

This is an exciting opportunity to shape the data landscape of Audit Technology and embed a unified data operating model across a complex and high‑growth portfolio.

Description of the role:
The Role The Head of Audit Data Governance is responsible for defining, ope rationalising, and continuously improving a holistic, enterprise‑aligned data operating model across the UK Audit business.

The role ensures that the people, processes, technology, and controls needed to manage data as a strategic asset are fully in place.

You will lead the four core pillars of the Audit Data:

Data Governance Establishing trust, ownership, accountability, policy, and lifecycle management.

Data Quality Ensuring data is accurate, complete, consistent, and continually monitored and improved.

Data as Insight Enabling actionable intelligence from data through reporting, analytics and trusted audit insights.

Data as a Service Ope rationalising data products, pipelines, and reusable data capabilities to support product teams and Audit delivery.

You will report to the Head of Audit Technology & Solutions and work across all Audit portfolios, collaborating with senior leaders to embed data excellence into product development, service operations, and the future Audit Target Operating Model.

Responsibilities Strategic Leadership Define and implement a unified Data Operations strategy aligned to the firm’s Enterprise Data Strategy and Audit Technology’s transformation roadmap.

Provide leadership across the four data pillars, ensuring cohesive delivery and standardisation across portfolios.

Shape the long‑term vision for data as a strategic asset within Audit, ensuring data underpins our growth, trust, AI adoption, and Audit Quality ambitions.

Represent Audit Technology in firmwide data governance forums and cross‑capability data initiatives.

Data Governance Establish and ope rationalise a robust governance framework, ensuring critical data assets are defined, catalogued, owned, and stewarded.

Lead business‑wide alignment of data roles, responsibilities, accountabilities and stewardship structures.

Develop and maintain policies and processes for managing data throughout its lifecycle.

Chair or oversee data governance forums, ensuring actions, risks and decisions are captured and enforced.

Data Quality Build and operate a data quality management capability—including profiling, monitoring, controls, remediation and reporting.

Identify and track data quality KPIs across portfolios and establish continuous improvement cycles.

Implement automated data quality tooling and standards across Engineering and Product teams.

Data as Insight Drive consistent reporting, dashboards and insight capabilities to support performance, risk management and audit delivery.

Partner with the Audit function and SMEs to translate operational and audit data into meaningful insight.

Define the operating model for insight development, including metadata management, lineage, and data interpretation standards.

Data as a Service Develop a scalable model for providing reusable, trusted, secure datasets, pipelines and APIs to product teams.

Work with Architecture, Engineering and Cloud teams to ope rationalise data platforms (e.g., Fabric, Informatica, Purview, Collibra). Establish service…