Build a reliable, scalable data platform
Connect and integrate new data sources into a unified pipeline
Orchestrate and ensure pipeline reliability: manage task dependencies, error handling, retry logic, and recovery from failures
Maintain data quality: build validation checks, handle NULLs and duplicates, monitor freshness and consistency
Prepare data as a product for AI agents: clean, documented, predictable datasets that can be trusted without manual verification
Contribute to analytical tasks where automation falls short, and support the team through the transition to self-service analytics

2+ years of hands-on experience as a Data Engineer or in a similar data infrastructure role
Strong SQL proficiency and practical experience working with cloud data warehouses (BigQuery preferred)
Experience designing and maintaining ETL/ELT pipelines and layered data warehouse architecture (raw → stage → final)
Hands-on experience with pipeline orchestration tools (Airflow, MWAA, or Cloud Functions): task dependencies, error handling, retry logic, failure recovery
Solid understanding of data quality practices: validation, NULL/duplicate handling, freshness and consistency monitoring
Bonus points: Experience in subscription-based products (web and/or mobile).

Data Engineer

Key skills