onsite
Data Engineer - Arlo
Data Engineer
Build scalable data pipelines and analytics solutions in AWS to power fraud detection, cost optimization, and member experience for a health‑insurance platform.
About the role
Key Responsibilities
- Design, develop, and maintain robust data pipelines using Python and SQL to ingest, transform, and store large volumes of healthcare and operational data.
- Implement and optimize ETL workflows on AWS services (Glue, Redshift, S3, Lambda) ensuring high availability and performance.
- Collaborate with data scientists and product teams to provide clean, well‑documented datasets for fraud detection models and cost‑analysis tools.
- Monitor pipeline health, troubleshoot issues, and implement automated alerts and logging for data quality and latency.
- Participate in data architecture discussions, proposing improvements to data models, storage strategies, and cost‑efficiency.
Requirements
- 3+ years of experience as a data engineer in a cloud environment.
- Strong proficiency in Python, SQL, and AWS data services.
- Hands‑on experience with ETL tools, data modeling, and performance tuning.
- Excellent problem‑solving skills and ability to work cross‑functionally.
- Knowledge of healthcare data standards (e.g., HL7, FHIR) is a plus.