Data Engineer

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

📋 Description

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

• Collaborate on Looker dashboards and LookML models in partnership with senior engineers and analysts.

• Create efficient, well-structured SQL for large-scale transformations within BigQuery.

• Implement data quality verification through Dataform assertions and automated notifications.

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

• Develop 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 familiarity with CDC concepts and event-driven data 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 bridge the gap between research prototypes and scalable, maintainable code.

⛳️ Requirements

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

• Experience with Dataform — or strong expertise in dbt with a readiness to work in Dataform; understanding of modular, version-controlled data transformation.

• Python proficiency with an engineering mindset — clean, tested, and linted code; comfortable using Git and CI/CD processes.

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

• Experience with orchestration tools — hands-on experience with Cloud Composer, Airflow, or similar tools.

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

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

• Collaborative and communicative — able to translate business requirements into data models and work effectively with Analytics, Product, and Data Science teams.

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

🏝️ Benefits

• Competitive salary.

• Meaningful equity.

• Pension Plan.

• Fully paid health insurance for employee and dependents.

• Life Assurance.

• Wellness Perk.

• Flexible workplace options including office-based, hybrid, and remote working.