Senior Manager Data Quality, UK Deloitte Data Office

Overview

In this role, you will lead the development and execution of Deloitte UK's enterprise data quality framework to ensure accurate, complete, and trustworthy data for AI and business decisions. You will partner with Data Owners, Data Stewards, and technical teams to remediate issues and promote a data-driven culture. Your work supports regulatory compliance, risk management, and the deployment of Generative AI and Agentic AI. This position offers impact across transformation initiatives and collaboration with cross-functional teams.

Pay / Benefits

• hybrid working policy
• world-class development and learning opportunities
• wellbeing-focused culture
• support for career progression
• collaboration across cross-functional teams
• flexible working arrangements

Responsibilities

• Define and implement the UK Data Office data quality strategy aligned with enterprise governance
• Create standard data quality frameworks covering quality dimensions, CDEs, and data quality rules
• Lead data profiling and root cause analysis to identify and remediate data quality issues
• Apply AI techniques to Data Quality Management and support data cleansing, enrichment, and standardisation
• Collaborate with Data Owners, Stewards, IT, and business stakeholders to prioritise and resolve issues
• Design and maintain data quality dashboards and reports for stakeholders and senior management
• Evaluate and implement data quality tools and automation to monitor and validate data (incl. unstructured data for GenAI)
• Train Data Owners and Stewards on data quality best practices and foster a data-driven culture
• Ensure data quality requirements are embedded in system implementations, migrations and AI model workflows

Key requirements

• Proven experience in data quality management and governance with leadership experience
• Proven track record of implementing enterprise-level data quality frameworks
• Strong understanding of data quality dimensions (accuracy, completeness, consistency, timeliness, validity, uniqueness)
• Proficiency with data profiling, cleansing, and standardisation tools (Informatica Data Quality, Talend Data Quality, Collibra, Ataccama or similar)
• Strong analytical and problem-solving skills with ability to identify root causes and propose practical remedies
• Solid understanding of data governance and its relation to data quality
• Awareness of data quality considerations for ML/GenAI, including bias and factual accuracy
• Excellent communication and stakeholder influencing skills
• Ability to manage multiple priorities in a dynamic environment

• Influence and collaboration with both technical and non-technical stakeholders
• Clear communication and presentation
• Problem-solving mindset
• Data quality tools (Informatica, Talend, Collibra, Ataccama)
• Data profiling and data cleansing techniques
• Knowledge of data governance principles

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