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