Head of Data Analytics

The Head of Data & Analytics is responsible for leading the organisation’s data strategy, governance, business intelligence, reporting, and data platform. The role exists to establish data as a strategic capability, ensure decisions are driven by high‑quality governed data, and build the foundations required for analytics, AI, and machine learning. This position is working for a high profile company.

Role Scope

You will lead all enterprise data functions, including:

• Data governance
• Business intelligence & reporting
• Data quality management
• Data platform operations
• Data engineering workflows

You will oversee the performance and evolution of the Power BI environment, enterprise data warehouse/lakehouse, and Azure data services. The role works closely with Finance, Operations, Commercial, Property, Business Change, Information Security, and technology partners. You will chair or co‑chair data governance forums and guide data stewards across business domains.

Key Responsibilities

You will be accountable for delivering:

• An enterprise data governance framework with clear ownership, quality standards, metadata management, and GDPR compliance
• High‑quality BI, executive dashboards, and board‑ready insights
• A secure, scalable, modern data platform with reliable ETL/ELT pipelines and strong SLAs
• Domain‑specific data products that support strategic priorities
• Governed, AI‑ready data for analytics, machine learning, and RAG pipelines
• Adoption of self‑serve analytics within defined guardrails

Knowledge, Skills & Experience

• Senior data leadership background
• Experience in infrastructure, telecoms, or asset‑intensive industries (preferred)
• Proven track record building or transforming Data & Analytics functions
• Deep expertise in data governance, data quality, metadata management, GDPR
• Strong Power BI capability (semantic models, DAX, dashboards, self‑serve)
• Experience with data warehouse/lakehouse architecture and Azure services (Data Factory, Synapse, Data Lake, SQL)
• Leadership of multidisciplinary data teams
• Strong stakeholder engagement and communication skills
• Budget management and ROI analysis experience
• Understanding of data requirements for AI/ML and RAG pipelines