Data Engineer

📋 Description

• Build and maintain ingestion pipelines for diverse data sources
• Design dbt models and transformation logic for clean source of truth tables
• Own pipeline orchestration with Dagster or Airflow
• Implement data quality monitoring and observability
• Collaborate with data science to support underwriting and pricing models
• Own projects end-to-end from scoping to deployment and monitoring

🎯 Requirements

• 3-5 years in data or backend engineering with pipelines
• Python and SQL production-grade code
• Dagster, Airflow, or Prefect experience
• dbt or equivalent transformation framework
• Cloud data environments AWS, GCP, or Azure
• Experience with messy real-world datasets
• Strong data quality instincts

🎁 Benefits

• High ownership and responsibility from day one
• Work on a mission that improves care at scale
• Fast growth and career opportunities
• Apply AI to meaningful healthcare problems
• Collaborative and fast-paced team culture
• Equity and growth opportunities