4 дня назад
Data Engineer (GCP)
Вакансия из Hirify Global, списка международных tech-компанийДля мэтча и отклика нужен Plus
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Data Engineer (GCP) (BigQuery, Dataform, Python): Building and evolving scalable data platforms, analytics models, and production pipelines for sports performance intelligence with an accent on data quality, orchestration, and collaboration with Data Science. Focus on designing medallion-architecture transformations, deploying tested ingestion workflows on GCP, and turning research prototypes into maintainable ML data pipelines.
Location: Remote from the United Kingdom
Company
develops a performance intelligence platform that helps sports organizations use data to improve athlete performance, analytics, and user experience.
What you will do
- Build and maintain BigQuery data models with Dataform using Bronze, Silver, and Gold medallion architecture patterns.
- Develop reliable Python data pipelines with testing, linting, and CI/CD integration.
- Schedule and monitor workflows with Cloud Composer or Airflow, and support data ingestion using CDC and event-driven patterns.
- Implement data quality checks, observability, freshness monitoring, and anomaly detection across the data warehouse.
- Containerize and deploy workloads with Docker on Cloud Run or similar GCP services.
- Support Data Scientists by productionizing research work and contributing to feature pipelines for ML workloads.
Requirements
- Strong SQL skills, including complex and performant queries in BigQuery.
- Dataform experience or strong dbt experience with willingness to work in Dataform.
- Python engineering experience with clean, tested, linted code, Git, and CI/CD workflows.
- Hands-on BigQuery and GCP experience, plus familiarity with Cloud Storage, Cloud Run, Pub/Sub, or Datastream.
- Experience with Cloud Composer, Airflow, or a comparable orchestration tool.
- Knowledge of data modeling, dimensional modeling, Kimball principles, medallion architecture, and Docker.
Nice to have
- Looker or LookML experience.
- Familiarity with CDC tools such as Datastream or Debezium.
- Exposure to ML frameworks or MLOps tools including scikit-learn, MLflow, or Vertex AI.
- AWS experience with services such as Redshift, Glue, or RDS.
- Interest in sports performance data.
Culture & Benefits
- Collaborate with Engineers, Data Scientists, Product, Analytics, and other stakeholders.
- Work remotely as part of a team building a platform used by sports teams and leagues worldwide.
- Use AI-assisted development pragmatically to improve productivity and code quality.
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