data engineering experience, with a strong track record of building and operating production data pipelines.
2+ years hands-on with BigQuery and GCP, with strong, demonstrable SQL — window functions, complex joins, and cost-aware query patterns.
Write and optimize BigQuery SQL transformations, models, and analytical queries with attention to correctness, performance, and cost.
Develop pipeline code in Python — ingestion, orchestration, testing, and packaging.
Implement data models across the raw, staging, curated, and semantic layers
Implement data quality, reconciliation, and validation checks so that incomplete or incorrect data cannot silently reach reporting.
Own the reliability of your pipelines — monitoring, alerting, freshness, and incident response for the data flows you build.
Optimize BigQuery cost and performance through partitioning, clustering, and efficient query patterns.
Follow and contribute to engineering standards version control, CI/CD, testing, documentation, and lineage and uphold them in code review.
Contribute to design discussions and propose approaches, while working within the architecture and standards set by the Data Lead.
Partner with finance and business stakeholders to understand reporting needs and translate them into durable, tested data models rather than one-off extracts.
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