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- Tasks: Build and maintain data pipelines for an elite sports organisation, transforming messy data into reliable systems.
- Company: Join a forward-thinking sports organisation that values innovation and teamwork.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Other info: Collaborative environment with passionate colleagues and a focus on continuous improvement.
- Why this job: Make a real impact on sports performance by shaping how data is used in decision-making.
- Qualifications: Strong Python and SQL skills, with experience in AWS and data engineering.
The predicted salary is between 50000 - 65000 £ per year.
Are you a Data Engineer who wants to build the data foundations of an elite sports organisation? If you're strongest when you're turning messy scripts into reliable pipelines, automating workflows, and designing cloud data systems that people actually trust then this role could be for you.
This is a core hire within a Data Team, working day-to-day with performance analysts, data scientists, and technical staff across the first team. You'll own key data pipelines, shape how data is engineered long term, and build systems that directly support on-pitch decision-making.
Why this role matters
Data is moving from isolated analysis into core football operations. This role sits at the centre of that shift. You won't just maintain pipelines — you'll help define:
- How data is ingested, modelled, and deployed
- How reliable, production-ready data supports performance insights
- How multiple football data sources are unified into one trusted platform
You'll have real ownership, visibility, and influence over how the data function evolves.
What you'll be responsible for
- Building, testing, and maintaining cloud-based ETL pipelines on AWS, ingesting data from APIs, web sources, and internal systems into Snowflake
- Refactoring and optimising Python and SQL workflows for speed, reliability, and scalability
- Automating pipelines and maintaining CI/CD, Git-based version control, and deployment standards
- Improving data modelling, storage efficiency, schema design, and partitioning to support scalable analysis
- Supporting the development of internal data tools and applications (e.g. Streamlit, Dash, or React-based apps)
- Integrating structured data with video and performance workflows
- Acting as the technical point of contact for external data providers
- Maintaining strong data governance, security, and GDPR-compliant practices
What we're looking for
- This role suits someone who is hands-on, curious, and comfortable owning production systems.
- Strong Python with demonstrable SQL
- Experience building and maintaining AWS-based data pipelines (Lambda, S3, Glue, Step Functions or similar)
- Experience working with Snowflake
- Experience with CI/CD and Git
- Comfortable working closely with analysts across multiple departments
- 2+ years' experience in a data engineering (or similar) role
Nice to have:
- Experience with football or sports datasets
- Experience with R
- Experience building data models for reporting tools
- Familiarity with GDPR and data governance best practice
The environment
- Working closely with analysts, data scientists, and performance staff
- Strong personalities, high standards, and a genuine interest in the game
- A culture that values being progressive, humble, determined, bright, and unified
Data Engineer employer: TRIA
Contact Detail:
TRIA Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those already working in data roles. Attend meetups or webinars related to data engineering and sports; you never know who might have a lead on your dream job!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving AWS, Python, and SQL. Share it on platforms like GitHub and make sure to highlight any work with sports datasets – it’ll catch the eye of hiring managers.
✨Tip Number 3
Prepare for interviews by brushing up on common data engineering challenges. Be ready to discuss how you've built and optimised pipelines, and don’t forget to mention your experience with CI/CD and Git. Practice makes perfect!
✨Tip Number 4
Apply through our website! We love seeing candidates who are genuinely interested in joining our team. Tailor your application to show how your skills align with the role, and let us know why you're passionate about data in sports.
We think you need these skills to ace Data Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the Data Engineer role. Highlight your experience with AWS, Python, and SQL, and don’t forget to mention any work with data pipelines or cloud systems.
Craft a Compelling Cover Letter: Use your cover letter to tell us why you’re passionate about data engineering in sports. Share specific examples of how you've turned messy scripts into reliable pipelines and how you can contribute to our team.
Showcase Your Projects: If you’ve worked on relevant projects, whether personal or professional, make sure to include them. We love seeing real-world applications of your skills, especially if they involve data modelling or automation.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to see your application and get to know you better. Plus, it shows you’re serious about joining our team!
How to prepare for a job interview at TRIA
✨Know Your Data Tools
Make sure you brush up on your knowledge of AWS, Snowflake, and Python. Be ready to discuss how you've used these tools in past projects, especially when building and maintaining data pipelines. Showing that you can turn messy scripts into reliable workflows will definitely impress.
✨Showcase Your Problem-Solving Skills
Prepare examples of how you've tackled challenges in data engineering. Whether it's optimising SQL queries or automating workflows, be specific about the problems you faced and the solutions you implemented. This will demonstrate your hands-on approach and technical expertise.
✨Understand the Role's Impact
Familiarise yourself with how data influences decision-making in sports. Be ready to discuss how your work as a Data Engineer can support performance insights and unify data sources. This shows that you’re not just technically skilled but also understand the bigger picture.
✨Be Ready for Technical Questions
Expect to dive deep into technical discussions during the interview. Brush up on your knowledge of CI/CD practices, Git version control, and data governance. Being able to articulate your experience and best practices will set you apart from other candidates.