Data Engineer

• 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, Scoreline is seeking a skilled Data Engineer to enhance and maintain the data infrastructure powering our AI-driven fantasy sports platform. This role involves designing efficient data pipelines, managing large-scale sports datasets, and ensuring seamless delivery of clean,..., Computer Vision Engineer (Sports Analytics) Location: Remote (UK-based) - occasional travel for key workshops Candidates must have proven sports analytics experience (match analysis, player metrics, tactical insights) as well as strong computer vision and deep..., Trainee Recruitment Consultant - Specialist Hedge Fund Headhunters Join a global specialist recruitment search firm working across Hedge Funds, Asset Management, Investment Banks, Crypto, and FinTech. Placing the most in-demand technologists, data scientists, engineers,..., Job Title: Programme Manager, Data & Technology Location: Hybrid - London (Southbank) Salary: £40,000.00 - £45,000.00 (depending on experience) About The Goat Agency Goat is part of WPP Media (formerly GroupM), the world's leading media investment company. Since 2015,...

• 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
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