Head of Data

Analytics, reporting and business intelligence

• Own the reporting estate and ensure Power BI, SSRS and QlikView solutions remain accurate, performant, governed and aligned to business definitions.
• Improve semantic models, data marts and self-service capability so teams can access trusted information without creating competing versions of the truth.
• Guide the transition from reactive reporting toward proactive insight, forecasting, exception monitoring and decision support.
• Maintain oversight of legacy reporting and applications while planning sensible modernisation and retirement pathways.

Data science, AI and intelligent automation

• Identify high-value use cases for machine learning, generative AI, computer vision, natural language processing, optimisation and robotic process automation.
• Lead the design, validation, deployment and monitoring of models such as propensity, customer segmentation, forecasting, similarity and recommendation, pricing, risk, RFV and sentiment analysis.
• Develop and govern LLM-enabled solutions including retrieval-augmented generation (RAG), vector databases, embeddings, document search, assistants, OCR workflows and knowledge tools.
• Ensure prototypes progress into maintainable products with defined ownership, quality controls, security, monitoring, fallback processes and measurable benefit.
• Evaluate internal and third-party AI tools, challenge vendor claims and select the most cost-effective solution for each use case.
• Promote responsible AI practices covering privacy, security, bias, explainability, human oversight and acceptable use.

Governance, security and compliance

• Maintain data governance standards covering ownership, lineage, definitions, retention, access, quality, classification and lifecycle management.
• Ensure compliance with UK GDPR, the Data Protection Act and company information-security policies.
• Implement robust role-based access controls, service-account standards, auditability and environment separation across data and AI platforms.
• Work with IT, Security, Legal and business owners to assess risk and ensure new solutions are introduced safely.
• Maintain accurate architecture, process, support and recovery documentation to a consistent professional standard.

Stakeholder and commercial management

• Build productive relationships with leaders and subject-matter experts across stores, ecommerce, finance, marketing, CRM, merchandising, operations and technology.
• Create clear business cases and prioritisation criteria for new initiatives, including effort, cost, risk, dependency, benefit and adoption requirements.
• Own or contribute to budgets, licensing decisions, cloud consumption management and supplier negotiations for the data and AI estate.
• Challenge requirements constructively, simplify solutions where possible and keep delivery focused on outcomes rather than technology for its own sake.
• Present recommendations, progress, risks and results in a concise and credible way to technical and non-technical audiences.

Experience and qualifications

Essential experience

• Substantial commercial experience spanning data engineering, data analytics and data science, with evidence of leading a broad data function or major cross-functional programmes.
• Proven experience managing and developing technical professionals, setting standards and delivering through others.
• Strong hands-on capability in SQL and Python, with the judgement to review designs, troubleshoot complex issues and guide engineering decisions.
• Experience designing, operating and improving enterprise data warehouses, lakehouses, data marts, pipelines and reporting platforms.
• Experience delivering database and platform migrations across cloud, on-premise and third-party systems.
• Practical experience with Microsoft Azure and Snowflake, together with strong knowledge of Microsoft SQL Server.
• Demonstrable experience setting up and running Snowflake in a commercial environment, including warehouse sizing, auto-suspend and auto-resume configuration, performance tuning, access-control design, monitoring and spend governance.
• Experience with orchestration tools such as Azure Data Factory, Prefect or Airflow.
• Strong experience administering or governing Power BI, SSRS and QlikView environments.
• Experience delivering machine-learning, AI or intelligent-automation solutions beyond proof-of-concept stage.
• Hands-on experience designing or delivering RAG solutions, including document ingestion, chunking, embeddings, vector database selection, retrieval quality, prompt orchestration, evaluation and monitoring.
• Strong understanding of data governance, security, privacy, quality and operational support.

Desirable experience

• Full-stack development experience, particularly where internal tools or data products require an effective user interface or API layer.
• Exposure to MongoDB and SQLite alongside relational database technologies.
• Exposure to VB or VBA, C#, HTML, CSS and JavaScript.
• Experience with GitHub, automated testing, CI/CD, infrastructure management and modern software-development practices.
• Retail, ecommerce, CRM, loyalty, customer, pricing, supply-chain or finance data experience.
• Experience evaluating and integrating third-party platforms, APIs, SaaS products, RPA tools or AI services.
• A degree or equivalent experience in Computer Science, Data Science, Mathematics, Engineering or a related discipline.

Initial priorities

• Review the current data estate, team capability, active commitments, technical risks and supplier landscape.
• Agree a prioritised roadmap for platform resilience, reporting improvement, data governance, AI and automation.
• Strengthen ownership, documentation, monitoring, testing, access control and support processes across the data estate.
• Progress the modern data-platform strategy and create a controlled migration and decommissioning plan for legacy components.
• Establish a repeatable route from AI or analytical idea to validated, secure and supportable production solution.
• Develop the team structure and skills plan required to increase proactive data science, AI and automation delivery.

Where will I be based? Fragrance Quarters, Trafford Park, Manchester.

How to apply: Simply upload your CV via our careers page.

Due to the high volume of applications that we receive, we are regrettably not able to respond to everyone. If you have not heard from us within four weeks of your application, please assume that on this occasion you have not been successful.