Data Engineer

About this role

Arlo, an AI-driven health insurance company, seeks a Data Engineer to build and maintain data pipelines that power underwriting and pricing models. You'll own data ingestion, transformation, quality monitoring, and collaboration with data science teams to ensure clean, reliable data flows across the organization.

What you'll do

• Build and maintain ingestion pipelines for diverse healthcare data sources including TPA feeds, claims, eligibility, and enrollment records
• Design dbt models and transformation logic that create authoritative data tables for underwriting, pricing, and reporting
• Implement pipeline orchestration using tools like Dagster or Airflow with monitoring, retries, and alerting
• Build data quality monitoring systems to catch duplicates, ID mismatches, enrollment gaps, and reporting delays
• Partner with data science teams to develop and maintain feature pipelines for ML models
• Document data quality limitations and work with engineering to prioritize fixes for upstream issues

What they're looking for

• Python and SQL (production-quality code)
• Pipeline orchestration tools (Dagster, Airflow, Prefect, or similar)
• dbt or equivalent data transformation frameworks
• Cloud data environments (AWS, GCP, or Azure)
• Columnar and analytical databases
• Data quality and observability practices
• Healthcare data or claims experience (nice to have)
• ML feature pipeline support (nice to have)