Most Loved Workplace® Certified JobSenior Data Engineer
Assessed by Most Loved Workplace®About the Role
At Garner Health, a Most Loved Workplace® certified employer in the Healthcare space, Transform healthcare by connecting patients with the best doctors through data-driven insights..
<div class="content-intro"><h2><strong>What you’ll be part of</strong></h2>
<p>Garner is on a mission to transform the U.S. healthcare system — and we’re the only proven player doing exactly that. We partner with employers to redesign how healthcare works: applying 550+ proprietary clinical metrics across 80+ specialties to a dataset of 320M+ patients to identify the best-performing doctors, then using compelling incentives to steer members to the care that helps them get healthier, faster.</p>
<p>The result is a rare “win win” — better care and lower costs for both members and employers. In just five years, our work has helped over 2.5 million people access higher-quality care and saved $1B in healthcare costs. We recently raised our Series E and have doubled five years running. If you've ever wanted your work to solve a problem that touches every person in this country, this is the opportunity to do exactly that. You'd be joining a team fundamentally reimagining healthcare in the U.S. — and using AI to scale that impact further and faster than anyone else can.</p></div><h3><strong>About the role:</strong></h3>
<p>We are seeking an exceptional Senior Data Engineer with a high sense of ownership who is excited about our mission, eager to learn and teach others, and can deliver across the tech stack. This role will report to our VP, Engineering. The ideal candidate should have experience with a modern data stack and implementations of data pipelines using Python and SQL in AWS.&nbsp;</p>
<h3><strong>Where you will work:</strong></h3>
<p>This role will be based in our New York City office. You must be willing to work in the office 3 days per week on Tuesday, Wednesday and Thursday.&nbsp;</p>
<h3><strong>What you will do:</strong></h3>
<ul>
<li>Build, optimize, and maintain data
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