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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer II - **Company:** DATA ENGINEERING, LLC - **Location:** United States (Remote available) - **Experience:** Experienced - **Salary:** $95,000.0 - $119,000.0 - **Contract:** Permanent contract - **Skills:** Clean Code Principles, Query Performance, Sql Data Warehouse, Airflow, BigQuery, Cluster Analysis, Data Validation, Information Engineering, Data Transformation, Data Systems, Python (Programming Language), Query Optimization, Software Engineering, Web Engineering, Data Pipelines - **Published:** August 15, 2026 - **Apply:** https://job-boards.greenhouse.io/splice/jobs/8707299002 ## About the Role * 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 ## Description We're looking for a Data Engineer II to join Splice's Data Engineering team and help scale the platform that powers creator payouts, revenue reporting, and product analytics across Splice's product lines. Data Engineering builds and maintains the reliable foundation that makes trusted data possible, enabling teams across Splice to work from a governed, consistent source of truth. We are accountable for the warehouse and pipeline foundation; ingestion, transformations, and the standards and quality guardrails that keep data consistent, timely, and usable. This is a mid-level, high-ownership role: engineers here carry features from technical design through delivery, monitoring, and documentation, and participate in our on-call rotation. The work requires hands-on data engineering experience. Our stack; BigQuery, SQLMesh, Python, Dagster- is distinct from Splice's web engineering stack, and effective contribution requires domain expertise in data pipeline systems, not general software engineering background., * 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 Reliability & Observability * 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 Finance & Revenue Pipelines * 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 Platform Quality & Optimization * 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 ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering) - [Making Data Warehouses fast. A developer's story.](https://www.wearedevelopers.com/videos/302-making-data-warehouses-fast-a-developer-s-story) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [Data Governance in the Era of AI](https://www.wearedevelopers.com/videos/1622-data-governance-in-the-era-of-ai) ## Related Articles - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [How We Built a Worry-Free System That Runs for 10+ Years – And What We’d Do Again](https://www.wearedevelopers.com/magazine/751-how-we-built-a-worry-free-system-that-runs-for-10-years-and-what-we-d-do-again) - [Fully Remote Software Engineer Jobs](https://www.wearedevelopers.com/magazine/447-fully-remote-software-engineer-jobs) - [Data Analyst Salary in the UK](https://www.wearedevelopers.com/magazine/278-data-analyst-salary-in-the-uk)