Data Engineer

Radiology is the second most used healthcare service, used by over 51% of the workforce annually. Despite the critical role of radiology in healthcare, the process for undergoing a medical imaging exam has remained unchanged for decades. OneImaging is solving this with a concierge approach and a premium-quality radiology network of over 5,000 vetted providers across 48 states, which also reduces imaging costs by 60-80%. Our solution helps patients and families access essential radiology services at fair prices and without surprise bills, all while delivering immediate savings and ROI for employers and payers on every exam.

We’re hiring Data Engineers graduating between December 2026 and June 2027 to join our data team in Miami, starting May or June 2027. This is not a rotational program and it isn’t a shadowing role. You’ll work on the pipelines and integrations that make OneImaging’s data the source of truth for the business - from the raw feed coming out of a payer, a provider, or our own platform, through the transformation logic, to the dashboard or automation that someone in operations, finance, or care navigation actually relies on every day.

It also means you’ll be building alongside a team that has moved unusually early on AI-assisted engineering. We run a shared AI harness that every engineer’s agent builds on, and we’re explicit internally that writing code is no longer the slow part of the job - the slow parts are deciding what to build and verifying what comes out. We’ll expect you to use these tools heavily and to own everything they produce for you.

What you'll do:

• Build and maintain data pipelines in Databricks (SparkSQL/PySpark) that ingest, transform, and validate data from sources like our platform databases, payer eligibility files, provider and claims systems, and third-party APIs - with a senior engineer as your mentor and reviewer
• Work across the full path a dataset takes - ingestion, transformation, modeling, and the Looker dashboard or downstream workflow it feeds - with guidance at first and increasing independence as you go
• Help build and maintain automated inbound/outbound file exchanges (eligibility, claims status, reporting) that other teams depend on to run their day-to-day operations
• Work with AI coding agents as a normal part of your workflow, and take full accountability for the output: you should be able to explain every file in your diff
• Write tests and validation checks for your pipelines, and treat data quality as part of shipping rather than a phase afterwards
• Participate in design reviews and code reviews from your first weeks - including reviewing other engineers’ work, because a bare approval with no comment isn’t a completed review here