Data Scientist (Sports Analytics
Rendel Limited
Manor Park, United Kingdom
11 days ago
Role details
Contract type
Permanent contract Employment type
Full-time (> 32 hours) Working hours
Regular working hours Languages
English Experience level
Senior Compensation
£ 45KJob location
Remote
Manor Park, United Kingdom
Tech stack
API
Data analysis
Google App Engines
Google BigQuery
Cloud Storage
Continuous Integration
Data Architecture
Information Engineering
ETL
Data Systems
DevOps
Data Flow Control
Python
Query Optimization
SQL Databases
Data Streaming
Google Cloud Platform
Data Ingestion
GIT
FastAPI
Data Lake
Kubernetes
Storage Technologies
Real Time Data
Machine Learning Operations
Api Design
Terraform
Data Pipelines
Serverless Computing
Apache Beam
Docker
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, 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,...
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
- DevOps/MLOps: Exposure to Terraform, Docker, Kubernetes, and MLOps workflows
About the company
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