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## About the company
COVU is a venture-backed technology startup transforming the insurance industry. We empower independent agencies with AI-driven insights and digitized operations, enabling them to manage risk more effectively. Our team is building an AI-first company set to redefine the future of insurance distribution.
Location:
This role can be hybrid or remote. If the candidate is based in the Los Angeles (LA) area, it will be a hybrid role working from our office in West Hollywood. For candidates based anywhere else in the US, this will be a fully remote role.
## The Role
We are looking for a crafty, execution-focused Data Engineer to join our Platform team. We've spent the last year building the foundation of COVU Connect - our proprietary data warehouse. Now, we are moving into a high-velocity phase: scaling the Golden Policy and Account records to power our AI-native operational platform, COVU OS.
This is not a role for someone who wants to spend months in "discovery." We need a builder who thrives in a defined architectural landscape, leverages AI tools (like Gemini-CLI) to ship code faster, and understands that speed-to-market is our most important KPI. You will work directly with our Lead Data Engineer to transform complex insurance logic into performant, automated pipelines.
## What You'll Do (The Mission)
- Execute the "Golden Records": Be the primary builder of the Golden Policy Journal and Golden Account Cluster. You will implement the harmonization and arbitration logic that turns messy carrier data into our single source of truth.
- AI-Augmented Development: Proactively use AI tooling (Gemini, Copilot, etc.) to accelerate ETL development, unit testing, and documentation. We value "smart speed."
- Build & Optimize Pipelines: Develop and maintain robust DAGs in Airflow and models in dbt to ensure our data is processed with high integrity and point-in-time accuracy.
- Operational Excellence: Implement "quarantine" logic for bad data and build reconciliation triggers to ensure our internal AMS matches our "Golden" state.
- Modernize & Refactor: Work within our Python-based framework to systematically replace legacy processes, ensuring every line of code is modular and SOC2 compliant.
- Collaborate via Agile: Participate in tight feedback loops with Product and Tech Leads to deliver comprehensive data integration.
## What We're Looking For
- 3–5 years of experience in data engineering. You've moved past the "learning" phase and are now focused on high-quality delivery. With demonstrated ownership of production pipelines - not just contributing to them.
- SQL & Python Fluency: You can write complex analytical SQL and clean, modular Python in your sleep.
- Modern Data Stack Experience: Hands-on experience with Snowflake and dbt.
- You understand how to build dimensional models that don't just store data but solve business problems.
- You've optimized queries, managed costs, not just run SELECT statements.
- You understand project structure, testing strategies, increment
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