Data Analyst

Data Analyst

• Salary: Competitive
• Location: Central London
• Sponsorship: Sponsorship is not available, so please only apply if you have the full, unencumbered right to work in the UK.

A large, complex organisation with a significant data and analytics function is looking for a Data Analyst to join its central Data & AI team.

This role will act as a key link between a central data platform team and a wider community of analysts across the business. You will help stakeholders define data challenges, build proof-of-concept solutions, support platform adoption, and contribute to the delivery of data-driven insights across multiple departments.

Key responsibilities

• Work with stakeholders to translate business questions into analytical use cases.
• Build proof-of-concept analyses and lightweight data solutions using Microsoft Fabric and Power BI.
• Develop simple end-to-end data models and identify when engineering support is required.
• Support UAT activities, testing documentation, and product rollouts.
• Provide updates on project progress, risks, and next steps.
• Support users with queries relating to Power BI, data models, and the analytics platform.
• Assist with data access requests and governance processes.
• Maintain platform documentation and training materials.
• Collaborate with analysts and subject matter experts to deliver cross-functional insights.

Requirements

• Degree in a STEM-related subject or equivalent commercial experience.
• Around 2-3 years' experience working with Microsoft technologies, including Power BI and Microsoft Fabric.
• Strong analytical and problem-solving skills.
• Experience supporting projects through development, testing, and production deployment.
• Confident communicator able to work with both technical and non-technical stakeholders.
• Experience within a large or multi-site organisation would be beneficial.
• PL-300 or similar Microsoft certification would be advantageous.

What's on offer

• Opportunity to work with a modern Microsoft data platform.
• Exposure to large-scale data products and a broad stakeholder community.
• A collaborative environment focused on data, analytics, and continuous improvement.