Data Engineer

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Kitman Labs

WebsiteLinkedInAll Job Openings

51 - 200 employees

⚽ Sports

🤖 Artificial Intelligence

💰 Series C on 2021-11

Sports • Artificial Intelligence • Analytics

Kitman Labs is a company dedicated to optimizing human achievement through advanced data intelligence and analytics. Founded and powered by practitioners and data scientists, the company focuses on providing a holistic, unified view of individual and organizational performance. Its all-in-one Intelligence Platform integrates thousands of data points to support leagues, clubs, teams, and governing bodies in reaching peak performance, particularly in sports and defense sectors. By leveraging proprietary technology and expertise, Kitman Labs helps to redefine and elevate performance outcomes through custom plans, data-driven strategies, and unified collaboration solutions. The company's mission is oriented towards winning trophies, extending careers, and solving significant challenges in performance and achievement.

📋 Description

• 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 • 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 • 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

🎯 Requirements

• 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

🏖️ Benefits

• Competitive salary • Health insurance for employee & dependants • Meaningful equity • Pension Plan • Life Cover • Income protection • Wellbeing benefits