Data Analyst – Motorsport

Silverstone
11 months ago
Applications closed

Related Jobs

View all jobs

Data Analyst

Data Analyst

Data Analyst

Data Analyst

Data Analyst

Data Analyst

Data Analyst – Motorsport

Silverstone | Up to £65,000 + Benefits DOE We're working with a high-profile motorsport team based in Silverstone who are looking for a Data Analyst to join their growing IT function. This role will support departments outside the FIA Financial Regulations, including Finance, HR, Commercial and Sustainability — so it’s your chance to make an impact behind the scenes of a top-tier racing operation.

This is an onsite, full-time role at their Silverstone HQ, with occasional travel.

Job Duties 
Build and manage Power BI dashboards and reports that deliver real insight

Work with stakeholders to understand data requirements and business goals

Design and maintain data models, pipelines and integrations

Handle data mapping, governance, and security

Take ownership of a BI Centre of Excellence – set best practices and support Power BI adoption across the business

Automate data flows and manage APIs

Support key functions by ensuring data reliability and availability

What They’re Looking For
Expert-level Power BI skills – storytelling, modelling (DAX), and visuals

Strong experience with SQL/TSQL and Azure tools – Data Factory, Synapse, Databricks, Data Lake, Delta Lake

Knowledge of Microsoft Fabric and Azure DevOps

Scripting in Python or C# a bonus (especially for advanced analytics)

Understanding of data governance (e.g. Purview)

Strong communicator – able to simplify the complex and influence non-technical stakeholders

Self-starter with a proactive, can-do attitude

Apply now or drop us a message for a confidential chat. We’ll walk you through the full spec and tell you why this is a cracking opportunity with a genuinely exciting team

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Products

Where to Advertise Machine Learning Jobs in the UK (2026 Guide)

Advertising machine learning jobs in the UK requires a different approach to most technical hiring. The candidate pool is small, highly specialised and in demand across AI labs, financial services, healthcare, autonomous systems and consumer technology simultaneously. Machine learning engineers and researchers move between roles through professional networks, conference communities and specialist platforms — not general job boards where ML roles compete with unrelated software engineering positions for the same audience. This guide, published by MachineLearningJobs.co.uk, covers where to advertise machine learning roles in the UK in 2026, how the main platforms compare, what employers should expect to pay, and what the data says about hiring across different role types.

Jobs

New Machine Learning Employers to Watch in 2026: UK and Global Companies Driving ML Innovation

Machine learning (ML) has transitioned from a specialised field into a core business capability. In 2026, organisations across healthcare, finance, robotics, autonomous systems, natural language processing, and analytics are expanding their machine learning teams to build scalable intelligent products and services. For professionals exploring opportunities on www.MachineLearningJobs.co.uk , understanding the companies that are scaling, winning investment, or securing high‑impact contracts is crucial. This article highlights the new and high‑growth machine learning employers to watch in 2026, focusing on UK innovators, international firms with significant UK presence, and global platforms investing in machine learning talent locally.

Careers

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.