Data Engineer

TRIA
West Midlands, UK
4 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Experienced
Experience required
2 years minimum
Working hours
Regular working hours

Tech stack

Application Programming Interfaces (APIs) Amazon Web Services Amazon S3 Continuous Integration Information Engineering Data Governance Extract Transform Load (ETL) Python (Programming Language) Standard Sql SQL Databases Systems Integration ReactJS
+8 more
Snowflake Git Build Tools Tools for Reporting Streamlit Framework Code Restructuring Software Version Control Data Pipelines

Job description

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

Requirements

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

Apply for this position

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Good distractions

Talks and stories from around this role — technically off-topic, practically not.

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Core technical practices for robust data engineering

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Balancing data science skillings alongside systems engineering rigor

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