Data Engineer II (Remote US)

Summary

Splice is a creative platform for music creators, offering sounds, samples, digital audio workstations, plugins, and AI-powered tools. The Data Engineer II will build and maintain data pipelines, transformations, and warehouse infrastructure supporting creator payouts, revenue reporting, product analytics, and reliable data systems. The role owns features from technical design through delivery, monitoring, documentation, and on-call support.

Responsibilities

• Build and maintain data models in SQLMesh, including incremental strategies, testing, and documentation
• Continuously improve and evolve our orchestration and transformation infrastructure as the platform scales
• Modernize legacy pipeline jobs in Python and SQLMesh, reducing technical debt over time
• Participate in on-call rotation; triage and resolve incidents including ETL failures, data unavailability, and core metric breakage
• Build introspectable software: define alert thresholds, emit metrics and logs, produce dashboards, and establish closed-loop escalation paths
• Improve observability across the platform so failures are caught early and resolved quickly
• Extend and maintain pipelines powering creator payouts and GAAP-compliant revenue reporting across Splice's product lines
• Build pipeline support for new revenue streams as Splice launches them
• Improve query performance and reduce compute costs in BigQuery
• Contribute to ingestion platform work and product analytics infrastructure
• Uphold our definition of done: validation complete, documentation updated, monitoring in place before closing a ticket

Skills

• 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

Qualifications

Must Haves

• 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

Benefits

• Equity opportunities
• Unlimited PTO to recharge and thrive.
• Comprehensive medical, dental, and vision coverage for you and your dependents.
• 401(k) plan with immediate vesting and company match.
• 12 weeks of fully paid parental leave for non-birthing parents, and 18-20 weeks for birthing parents.
• Work remotely or connect at our office hubs and creative spaces worldwide.
• Annual learning budget, leadership programs, and team ambassador opportunities.
• Inclusive events, team meet-ups, and vibrant Employee Resource Groups.