Data Engineer

This is a fully remote position, open to applicants in United Kingdom.

📋 Description

• Develop and maintain BigQuery data models utilizing Dataform, adhering to medallion architecture patterns (Bronze/Silver/Gold).

• Collaborate on Looker dashboards and LookML models alongside senior engineers and analysts.

• Craft efficient, well-organized SQL for large-scale transformations within BigQuery.

• Implement data quality checks via Dataform assertions and automated notifications.

• Ensure data observability across the warehouse by monitoring pipeline health, data freshness, and detecting anomalies.

• Construct and sustain robust Python data pipelines, incorporating testing, linting, and CI/CD integration.

• Utilize orchestration tools (Cloud Composer / Airflow) to schedule and oversee workflows.

• Gain knowledge of CDC concepts and event-driven ingestion patterns (Datastream, Pub/Sub).

• Containerize workloads using Docker for deployment on Cloud Run or similar GCP services.

• Assist Data Scientists in transitioning work from notebooks to production pipelines.

• Contribute to feature pipelines and data preparation for machine learning workloads.

• Help transition research prototypes into scalable, maintainable code.

⛳️ Requirements

• Proficient in SQL — comfortable crafting complex, efficient queries against large datasets in BigQuery.

• Experience with Dataform — or strong dbt background with a willingness to adapt to Dataform; familiar with modular, version-controlled data transformations.

• Python proficiency with an engineering perspective — producing clean, tested, and linted code; adept with Git and CI/CD workflows.

• Familiarity with GCP — hands-on experience with BigQuery is required; broader knowledge of GCP services (Cloud Storage, Cloud Run, Pub/Sub, Datastream) is a significant advantage.

• Experience with orchestration tools — practical experience with Cloud Composer, Airflow, or a similar platform.

• Understanding of data modeling fundamentals — including dimensional modeling, Kimball principles, or medallion architecture patterns.

• Basic knowledge of Docker — capable of containerizing and deploying data workloads.

• Collaborative and communicative — skilled at translating business requirements into data models and working effectively with Analytics, Product, and Data Science teams.

• Pragmatic approach to AI tools — comfortable leveraging AI-assisted development to enhance productivity and code quality.

🏝️ Benefits

• Competitive salary.

• Health insurance coverage for employees and their dependents.

• Meaningful equity opportunities.

• Pension plan.

• Life insurance coverage.

• Income protection.

• Wellbeing benefits.