Lead Data Engineer

Join Us! HealthCare.com has become one of America’s fastest-growing insurtech companies, revolutionizing how consumers shop for health insurance. Leveraging advanced technology and data science, the company has developed customized proprietary products to better fit consumer requirements, enhance customer satisfaction, and take some of the guesswork and inefficiencies out of buying insurance. About the Role We’re hiring a Data Engineer to help own and scale our core data platform. This role is hands-on and production-focused: you’ll design, build, and maintain data pipelines that power analytics, machine learning, and operational systems. We’re especially interested in candidates who combine strong data engineering fundamentals with either analytics depth or DevOps / platform experience. What You’ll Do Design, build, and maintain production-grade data pipelines using Airflow and AWS services like Lambda, DynamoDB Own data ingestion from internal systems and third-party integrations (e.g., Google, Bing, external APIs). Manage data storage and movement across S3, Snowflake, Snowpipe, and DynamoDB. Write and maintain custom Python code that runs reliably in production. Work across dev, staging, and production environments with proper deployment and rollback practices. Partner with analytics, data science, and product teams to design reliable, usable data models. Review code, mentor junior engineers, and help establish best practices for data quality, reliability, and observability. Identify and fix performance, cost, or reliability issues in existing pipelines. What We’re Looking For

Core Requirements

Strong experience building and maintaining production data pipelines.

Deep comfort with Python for data engineering (not just scripting).

Hands-on experience with Airflow in a real production environment.

Experience working in AWS, including S3 and managed services.

Solid SQL skills and experience working with analytical warehouses (Snowflake strongly preferred).

Experience operating systems across multiple environments (dev / prd).

Ability to mentor others through code review, design discussions, and troubleshooting.

Bonus Skills

Experience with Kubernetes or containerized workloads.

DevOps or platform experience (CI/CD, infrastructure-as-code, monitoring).

Analytics experience (data modeling, working directly with analysts or stakeholders).

Experience integrating with external APIs and managing schema or contract changes.

History of improving data reliability, latency, or cost at scale.

Experience as a technical mentor—reviewing code, setting standards, and helping the team make better engineering decisions

Can explain why a system is built a certain way, not just how.