Data Engineer II (Remote US)
$94,952–$118,690 year
RemoteUnited States
Job Summary
Build and maintain data models in SQLMesh, including incremental strategies, testing, and documentation. Continuously improve orchestration infrastructure and modernize legacy pipeline jobs in Python and SQLMesh to reduce technical debt. Participate in on-call rotation to triage ETL failures and data unavailability, while defining alert thresholds and establishing closed-loop escalation paths. Extend pipelines powering creator payouts and GAAP-compliant revenue reporting, and improve query performance in BigQuery to reduce compute costs. Uphold validation, documentation, and monitoring before closing tickets. This mid-level, high-ownership role carries features from technical design through delivery within a small, embedded platform team supporting finance-critical processes and product analytics.
Required Qualifications
- 3+ years of hands-on data engineering experience in a production environment
- Proficiency in SQL — window functions, CTEs, query optimization, execution plan analysis
- Proficiency in Python for pipeline logic, data transformation, and testing (maintainable code, not just scripts)
- Experience with a modern transformation framework — SQLMesh, dbt, or equivalent — including incremental models, testing, and documentation
- Production experience with a cloud data warehouse (we use BigQuery); understands partitioning, clustering, and cost management
- Experience with at least one workflow orchestrator (Dagster, Airflow, Prefect, or equivalent)
- Demonstrated ability to build observable, reliable data systems — alerting, dashboards, and data quality checks
- Comfortable owning small-to-medium features from technical design through delivery with limited guidance
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