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