Staff Data Engineer

<div class="content-intro"><p><span style="font-family: verdana, geneva, sans-serif; font-size: 12pt;"><strong><span data-contrast="none">Who We Are</span></strong></span></p> <p><span style="font-family: verdana, geneva, sans-serif; font-size: 12pt;">Imagine Pediatrics is a tech enabled, pediatrician led medical group reimagining care for children with special health care needs. We deliver 24/7 virtual first and in home medical, behavioral, and social care, working alongside families, providers, and health plans to break down barriers to quality care. We do not replace existing care teams; we enhance them, providing an extra layer of support with compassion, creativity, and an unwavering commitment to children with medical complexity.</span></p></div><p><span style="font-family: verdana, geneva, sans-serif; font-size: 12pt;"><strong><span data-contrast="none">What You’ll Do</span></strong><span data-ccp-props="{"134233117":true,"134233118":true,"201341983":0,"335559739":160,"335559740":240}"> </span></span></p> <p><span style="font-family: verdana, geneva, sans-serif; font-size: 12pt;"><span data-contrast="auto">As a Staff Data Engineer at Imagine Pediatrics, you will be the first dedicated Data Engineer on a hybrid team with Analytics Engineers, responsible for defining how data moves through our platform and owning the data pipelines that power clinical analytics, operational reporting, and external integrations.</span><span data-ccp-props="{"335559739":200}"> </span></span></p> <p><span style="font-family: verdana, geneva, sans-serif; font-size: 12pt;"><span data-contrast="auto">You will ensure that data ingestion and integration decisions are made with a clear understanding of downstream analytical usage, including how data freshness, grain, and structure impact downstream processes and systems. You will partner closely with Analytics Engineers, Product Engineers and Platform Engineers to deliver a platform built for a high-growth, mission-driven healthcare organization. This role requires strong technical depth in data engineering, comfort operating in ambiguous problem spaces, and the ability to influence across engineering and product teams.</span><span data-ccp-props="{"335559739":200}"> </span></span></p> <ul> <li style="font-family: verdana, geneva, sans-seri