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Splice is a creative platform for music producers, offering a subscription service with an industry-leading catalog of sounds, samples, and an expanding AI stack. The company also provides a rent-to-own marketplace for DAWs and plugins that integrate seamlessly into any music production workflow.
You'll join Splice's Data Engineering team, a small embedded platform team responsible for the pipelines, transformations, and warehouse infrastructure that powers the entire company. The team supports finance-critical processes (contributor payouts, GAAP revenue reporting), product analytics, and data reliability for customer-facing features like recommendations. The team operates with a shared on-call rotation and prioritizes observable, well-documented, durable systems.
This is a mid-level, high-ownership role where you'll carry features from technical design through delivery, monitoring, and documentation. You'll work with BigQuery, SQLMesh, Python, and Dagster—a distinct stack from Splice's web engineering.
Key responsibilities include:
- Building and maintaining data models in SQLMesh with incremental strategies, testing, and documentation
- Modernizing legacy pipeline jobs in Python and SQLMesh to reduce technical debt
- Participating in on-call rotation to triage and resolve ETL failures, data unavailability, and metric breakage
- Building introspectable software with alert thresholds, metrics, logs, dashboards, and escalation paths
- Extending and maintaining pipelines for creator payouts and GAAP-compliant revenue reporting
- Improving query performance and reducing compute costs in BigQuery
- Contributing to ingestion platform and product analytics infrastructure
Requirements: 3+ years of hands-on data engineering in production, proficiency in SQL (window functions, CTEs, query optimization, execution plan analysis), and proficiency in Python for pipeline logic, data transformation, and testing.
