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Pie Insurance is transforming commercial insurance for small businesses through technology. This is a hands-on Senior Data Engineer role focused on building and maintaining the data infrastructure that powers quoting, underwriting, and servicing operations.
You'll write production Python and SQL, design Airflow DAGs, and contribute to a Data Vault 2.0 warehouse alongside a team of staff engineers. The pipelines and models you build feed critical business functions—from pricing to financial reporting—where correctness and reliability are paramount.
Key responsibilities include:
- Developing complex, efficient data pipelines that transform raw data into reliable, well-tested data models
- Designing and maintaining data pipelines with the freshness and accuracy stakeholders depend on
- Making data modeling decisions within Data Vault 2.0 that balance raw fidelity with downstream consumption patterns
- Administering and optimizing Snowflake (warehouse sizing, query performance, RBAC, cost tuning)
- Building and maintaining resilient Airflow DAGs and CI/CD pipelines
- Implementing automated testing (unit, integration, data quality) to catch issues before production
- Owning production observability, tuning alerts, responding to incidents, and closing feedback loops
- Leveraging AI-powered tools (Claude Code, Cursor, Snowflake Cortex) as core development workflow components
- Translating business requirements into technical solutions by working across Executive, Product, Engineering, and business teams
- Leading technical projects end-to-end without a Product Manager—scoping, documenting, and explaining trade-offs
- Driving cross-team initiatives requiring influence and alignment
- Establishing best practices for data governance, privacy, security, and SOX-relevant reporting
- Participating in operational responsibilities for data infrastructure reliability and cost efficiency
Required qualifications:
- Minimum 5 years as a software or data engineer focused on data systems
- Advanced SQL proficiency and experience manipulating large structured/semi-structured datasets
- Production-grade Python for data pipelines
- Hands-on Snowflake administration (warehouse management, RBAC, access controls, cost governance)
- Experience designing and implementing modern data warehouses
- Cloud data warehouse modeling (Snowflake, Redshift, or BigQuery); Data Vault 2.0 strongly preferred
- Testing frameworks for data and code validation in production
- Data observability tooling experience
- Proficiency with AI coding assistants as core workflow tools
- Track record leading technical projects end-to-end
- Comfort in regulated environments (SOX-relevant financial reporting)
- Willingness to develop deep domain expertise in insurance and Pie's business
The role emphasizes that successful engineers understand insurance concepts (premium, loss, policy lifecycle) as well as they understand Snowflake.
