Data Engineer (Football Club)

About the Opportunity

This is a unique opportunity for a Data Engineer to work at the intersection of cutting-edge technology and elite sports performance. You'll join a collaborative, high-standard engineering team with a culture built around creativity, innovation, and excellence.

In this role, you'll play a key part in designing and developing scalable data pipelines and infrastructure that directly impacts decision-making at the highest levels of the football world—including performance insights for some of the most well-known footballers in the industry.

This is the perfect environment for those passionate about leveraging advanced data engineering to drive real-world results in sports analytics.

Key Responsibilities

• Architect, design, build, test, and maintain scalable and high-performance data pipelines
• Ensure all systems adhere to best practices for data quality, integrity, and security
• Integrate modern data engineering tools and technologies into cloud-native infrastructure
• Develop tools and solutions to support sports data modeling, analytics, and predictive insights
• Collaborate with data scientists to enable end-to-end data workflows
• Own the architecture and maintenance of a GCP-based data lake/lakehouse environment

Your Background

• 4+ years of industry experience in Data Engineering roles
• Advanced-level Python for data applications and high proficiency in SQL (query tuning, complex joins)
• Hands-on experience designing and deploying ETL/ELT pipelines using Google Cloud Dataflow (Apache Beam) or similar tools
• Proficiency in data architecture, data modeling, and scalable storage design
• Solid engineering practices: Git and CI/CD for data systems

Highly Desirable Skills

• GCP Stack: Hands-on expertise with BigQuery, Cloud Storage, Pub/Sub, and orchestrating workflows with Composer or Vertex Pipelines.
• Domain Knowledge: Understanding of sports-specific data types (event, tracking, scouting, video)
• API Development: Experience building data-centric APIs using FastAPI, especially in serverless environments (e.g., Google App Engine)
• Streaming Data: Familiarity with real-time data pipelines and data ingestion at scale
• DevOps/MLOps: Exposure to Terraform, Docker, Kubernetes, and MLOps workflows

What They Offer

• A chance to work on real-world data that impacts elite football performance
• Access to high-value datasets, sports science teams, and cross-disciplinary experts
• A flexible hybrid working model (1 day per month in the London office)
• The opportunity to grow within a digital-first team at a world-renowned football club
• The satisfaction of applying your engineering skills in an environment where your work directly influences results on the pitch