Data Scientist (Sports Analytics
Role details
Job location
Tech stack
Job description
- 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, ️ Senior Bridge Engineer | London | Shape the Future Are you ready to lead the charge on ground breaking bridge projects that will shape the world? At Rendel, part of the global Ingérop Group, we've been delivering innovative engineering solutions for over 180 years....
Director of Data and Analysis
Rising Ballers
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Requirements
- 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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