Location/Remote: 100% remote within the United States; must be willing to work Eastern Time Zone hours

Employment Type: Permanent / Direct Hire / Full-time

Compensation: up to $160k base salary (depending on experience)

Benefits

• Full healthcare coverage for employee + family (medical, dental, vision, life, and supplemental insurances)
• Short- and Long-Term Disability (STD/LTD)
• HSA & FSA options
• Unlimited PTO
• Stock Options
• 401(k)

About the Role

We're hiring a Data Engineer to help build and scale a modern, cloud-native data platform. You'll be hands-on with Databricks, PySpark, and AWS to build, deploy, and manage production-grade pipelines from the ground up.

We’re looking for someone who thrives in a high-autonomy environment, wants to take ownership of their work, and is excited about working in a fast-paced, healthcare-adjacent startup.

What You’ll Do

• Design and develop scalable, production-ready data pipelines using Databricks, PySpark, Python, and SQL
• Deploy and maintain pipelines on AWS, using S3, EMR, and Glue
• Own systems end-to-end — from ingestion and transformation to production deployment
• Contribute to the design of new data models and derived metrics sold to clients
• Collaborate closely with analytics, product, and engineering teams to meet customer-facing data needs
• Review and improve existing pipeline architecture and performance

What We’re Looking For

• 5+ years of experience in data engineering or equivalent production-facing pipeline work
• Strong Python programming and PySpark experience — not just SQL
• Strong experience with Databricks or similar big data platforms
• Proven ability to build and deploy data pipelines independently
• Experience working with AWS data services (e.g., S3, EMR, Glue)
• DBT experience is a bonus
• Background in healthcare data is helpful, but not required — must be open to learning