At a Glance
- Tasks: Build and evolve our data platform, transforming raw data into reliable insights.
- Company: Join Kitman Labs, a leader in sports performance intelligence and innovation.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Collaborative team environment with a passion for sports and data.
- Why this job: Make an impact in the sports industry by working with top athletes' data.
- Qualifications: Proficient in SQL, Python, and familiar with GCP and data modelling.
The predicted salary is between 60000 - 80000 £ per year.
Kitman Labs is the performance intelligence company, disrupting and transforming the way the sports industry uses data to unlock the potential of the world's top athletes. Driven by a passion to innovate in the areas of sports performance, analytics and user experience, we have assembled a team of the industry's top data scientists, sports performance scientists, product specialists and engineers. Kitman Labs' advanced Intelligence Platform (iP) is now used by over 2000 teams in 50 leagues on 6 continents, including the NFL, Premier League, National Women's Soccer League and MLS.
We're looking for a Mid-Level Data Engineer to join our team and help build and evolve our data platform. You'll work across analytics engineering, data pipelines, and data quality — collaborating closely with Engineers, Data Scientists, and Product to turn raw data into reliable, scalable foundations.
What You'll Work On
- Analytics Engineering & Reporting
- Build and maintain BigQuery data models using Dataform, following medallion architecture patterns (Bronze/Silver/Gold)
- Contribute to Looker dashboards and LookML models, working alongside senior engineers and analysts
- Write performant, well-structured SQL for large-scale transformations in BigQuery
- Implement data quality checks using Dataform assertions and automated alerting
- Support data observability across the warehouse — monitoring pipeline health, data freshness, and anomaly detection
- Data Pipelines & Ingestion
- Build and maintain robust Python data pipelines with testing, linting, and CI/CD integration
- Work with orchestration tooling (Cloud Composer / Airflow) to schedule and monitor workflows
- Develop familiarity with CDC concepts and event-driven ingestion patterns (Datastream, Pub/Sub)
- Containerise workloads with Docker for deployment on Cloud Run or similar GCP services
- Data Science Collaboration
- Support Data Scientists in moving work from notebook to production pipeline
- Contribute to feature pipelines and data preparation for ML workloads
- Help bridge the gap between research prototypes and scalable, maintainable code
What We're Looking For
- SQL proficiency — comfortable writing complex, performant queries against large datasets in BigQuery
- Dataform experience — or strong dbt experience with willingness to work in Dataform; understanding of modular, version-controlled data transformation
- Python with an engineering mindset — clean, tested, linted code; comfortable with Git and CI/CD workflows
- GCP familiarity — hands-on experience with BigQuery is essential; broader GCP exposure (Cloud Storage, Cloud Run, Pub/Sub, Datastream) is a strong advantage
- Orchestration experience — hands-on with Cloud Composer, Airflow, or a comparable tool
- Data modelling fundamentals — dimensional modelling, Kimball principles, or medallion architecture patterns
- Docker basics — able to containerise and deploy data workloads
- Collaborative and communicative — able to translate business requirements into data models and work effectively with Analytics, Product, and Data Science stakeholders
- Pragmatic approach to AI tooling — comfortable using AI-assisted development to improve productivity and code quality
Nice to have
- Looker / LookML experience
- Familiarity with CDC concepts and tools (Datastream, Debezium)
- Exposure to ML frameworks or MLOps tooling (scikit-learn, MLflow, Vertex AI)
- AWS experience as a complement (Redshift, Glue, RDS) — we value engineers who can draw on cross-cloud perspective
- Curiosity about sports performance data
Data Engineer employer: Kitman Labs
At Kitman Labs, we are not just transforming the sports industry; we are also committed to fostering a vibrant and inclusive work culture that prioritises employee growth and innovation. As a Remote Senior Frontend Engineer, you will join a dynamic team dedicated to pushing the boundaries of sports performance analytics, with access to competitive salaries, comprehensive health benefits, and meaningful equity opportunities. Our collaborative environment encourages continuous learning and mentorship, making Kitman Labs an exceptional place for those looking to make a significant impact in their careers.
