Job Description

Staff Data Engineer

at Garner Health


Garner’s mission is to transform the healthcare economy, delivering high quality and affordable care for all. By helping employers restructure their healthcare benefit to provide clear incentives and data-driven insights, we direct employees to higher quality and lower cost healthcare providers. The result is that patients get better health outcomes while doctors are rewarded for practicing well, not performing more procedures. We are backed by top-tier venture capital firms, are growing rapidly and looking to expand our team.

We are looking for a hands-on Staff Data Engineer to join our data engineering team and drive the implementation of pipelines which deliver the insights core to our business. The ideal candidate should have experience with a modern data stack and implementations of data pipelines using Python in AWS. They should be excited about collaborating with data scientists to bring their research to life.

Main Responsibilities:

  • Build and maintain data pipelines delivering core insights
  • Collaborate with data scientists to productionize research results
  • Protect our users’ privacy and security through best practices
  • Delivering insights via our data warehouse
  • Support pipelines in production
  • Assist in task planning, estimation, scheduling, and staffing
  • Mentor junior and mid-level engineers
  • Grow engineering teams by interviewing, recruiting, and hiring

Our Tools:

  • Python, AWS, Terraform, Snowflake, Git

Ideal Qualifications:

  • 7+ years hands-on work building data pipelines and internal applications
  • Expertise in Python
  • Comfortable leading research and development projects that produce new designs, products, and processes
  • Comfortable checking the team’s work for technical accuracy
  • Ability to coordinate work with managers and other staff
  • Experience working with an orchestration tool such as Airflow, Argo, Prefect, or Dagster
  • Familiarity with healthcare or insurance
  • Experience with one or more database warehouses, especially Snowflake