Staff Software Engineer, Data Engineering

Staff Software Engineer, Data Engineering

This job is no longer open

About us

Traditional health care is broken. Galileo is here to fix it. We’re a rapidly growing health startup that combines intuitive design and clinical expertise to deliver affordable, quality care for all.

 

Galileans, as we like to call ourselves, are dedicated to flipping the traditional healthcare model into a modern solution for today—and beyond. Our empathetic, mission-driven culture puts our patients first, celebrates creative problem-solving, and moves quickly to build great products. Our teams work collaboratively, so there’s plenty of day-to-day interaction. We believe in a hybrid, flexible working environment and have team members across the U.S. and the UK.

 

Galileo is looking for a Staff Software Engineer to join our data engineering team. In this role, you will be part of a new team building a data platform that builds the foundation for materially improving provider productivity and fostering more desirable health outcomes.  We are looking for engineers who enjoy the freedom to act creatively in a collaborative environment and further develop their data engineering mastery to make healthcare a better experience for all involved.

 

Here's what you’ll do:

 

  • Have significant opportunities to shape a new best-in-class healthcare data platform from architecture to development practices.
  • Collaborate closely with clinicians, analysts, and other engineers to create insights and actions through your continued mastery of data engineering principles
  • Build deep expertise in healthcare data standards and interoperability across clinical, financial, and operational disciplines.
  • Be part of a team of seasoned engineers dedicated to technical excellence, great design, simplicity, automation, and helping others.

 

We'd love to hear from you if you have the following:

 

  • 9+ years of professional experience as a software and/or data engineer 
  • Demonstrated experience with a variety of ETL/ELT pipelines in both batch and near-real-time latencies 
  • Strong software engineering skills with the ability to design, implement, test, deploy and monitor functionality
  • Strong understanding of analytical databases such as Redshift and Snowflake
  • Demonstrated experience building and operating data architecture with respect to latency, reliability, consistency, security, and cost requirements.
  • Clear communication of technical concepts with the ability to collaborate with engineering and other parts of the organization
  • A desire to learn, grow, and enjoy the responsibility and accountability that comes with high levels of ownership and autonomy

 

Bonus points if you also have:

  • Experience integrating HL7-compliant data (e.g., C-CDA or FHIR)
  • Familiarity with modern analytics databases like Redshift and Snowflake
  • Familiarity with healthcare data domains, including insurance claims, enrollment, electronic health records, risk adjustment, or HEDIS quality
  • Experience scaling in a startup environment

 

Compensation range:  

 

$144,000 - $216,000 based upon prior experience, performance, and market dynamics

 

Benefits

  • Medical / Dental / Vision insurance
  • Flexible Spending Account
  • Health Savings Account + match
  • Company paid STD/LTD, AD&D, and Life insurance
  • Paid Family Leave
  • 401K + match
  • Paid Time Off

 

How we hire

Galileo is committed to hiring the best team possible to build health care that works for everyone. We value a diverse set of perspectives to deliver the best possible solutions to those problems. We look for talent from a wide range of backgrounds—including, but not limited to—race, age, sexual orientation, gender identity, and expression, national origin, religion, disability, and veteran status. Galileo is an Equal Opportunity Employer and provides reasonable accommodations to applicants and employees with a qualifying disability or conflict with a sincerely held religious belief unless doing so would cause an undue hardship or fail to eliminate a direct threat.

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