Central London, London, United Kingdom Hybrid / WFH Options
Singular Recruitment
Python for data applications and high proficiency SQL for complex querying and performance tuning. ETL/ELT Pipelines: Proven experience designing, building, and maintaining production-grade data pipelines using Google Cloud Dataflow (Apache Beam) or similar technologies. GCP Stack: Hands-on expertise with BigQuery , Cloud Storage , Pub/Sub , and orchestrating workflows with Composer or Vertex Pipelines. Data Architecture … Experience: Familiarity with the unique structure of sports data (e.g., event, tracking, scouting, video). API Development: Experience building data-centric APIs, especially with FastAPI on serverless platforms like GoogleAppEngine . Streaming Data: Practical experience building real-time data pipelines. DevOps & MLOps: Knowledge of Infrastructure as Code (Terraform), MLOps principles, and containerization (Docker, Kubernetes). More ❯
City of London, London, United Kingdom Hybrid / WFH Options
Singular Recruitment
Python for data applications and high proficiency SQL for complex querying and performance tuning. ETL/ELT Pipelines: Proven experience designing, building, and maintaining production-grade data pipelines using Google Cloud Dataflow (Apache Beam) or similar technologies. GCP Stack: Hands-on expertise with BigQuery , Cloud Storage , Pub/Sub , and orchestrating workflows with Composer or Vertex Pipelines. Data Architecture … Experience: Familiarity with the unique structure of sports data (e.g., event, tracking, scouting, video). API Development: Experience building data-centric APIs, especially with FastAPI on serverless platforms like GoogleAppEngine . Streaming Data: Practical experience building real-time data pipelines. DevOps & MLOps: Knowledge of Infrastructure as Code (Terraform), MLOps principles, and containerization (Docker, Kubernetes). More ❯
london (city of london), south east england, united kingdom Hybrid / WFH Options
Singular Recruitment
Python for data applications and high proficiency SQL for complex querying and performance tuning. ETL/ELT Pipelines: Proven experience designing, building, and maintaining production-grade data pipelines using Google Cloud Dataflow (Apache Beam) or similar technologies. GCP Stack: Hands-on expertise with BigQuery , Cloud Storage , Pub/Sub , and orchestrating workflows with Composer or Vertex Pipelines. Data Architecture … Experience: Familiarity with the unique structure of sports data (e.g., event, tracking, scouting, video). API Development: Experience building data-centric APIs, especially with FastAPI on serverless platforms like GoogleAppEngine . Streaming Data: Practical experience building real-time data pipelines. DevOps & MLOps: Knowledge of Infrastructure as Code (Terraform), MLOps principles, and containerization (Docker, Kubernetes). More ❯
