OneImaging

Associate Data Engineer

USA new gradAI/ML/DataPosted 24 days ago

Location: Miami, FL
Type: USA new grad

About this role

From OneImaging’s careers page.

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
Ask why. We reason from first principles and we have an explicit norm that engineers are not implementation machines - if a requirement doesn’t make sense, we want you to say so
Handle protected health information correctly, with data governance, access controls, and audit logging as first-class requirements rather than afterthoughts

About you:

Graduating with a B.S. or M.S. in Computer Science, Data Science, Computer Engineering, or a related technical discipline between December 2026 and June 2027
You’ve built things nobody assigned you - side projects, coursework you took further than required, hackathon work, something with real data, however small
Strong SQL skills and working knowledge of Python for data processing
Some exposure to Databricks, Spark, or a similar distributed data processing tool - coursework, an internship, or a personal project is enough; we don’t expect production experience
A basic mental model of how data moves from a source system into a warehouse or lakehouse and out to a report
You use AI coding tools and you’ve formed opinions about them - including where they mislead you and how you catch it
You can explain a technical decision you made and what you’d do differently, which matters more to us than the sophistication of the project
Comfortable with ambiguity and with being told “we haven’t figured that out yet”
Intellectually honest: you can change your mind when the evidence changes, and you’d rather delete your own work than defend it
Clear written and verbal communication - you’ll be writing documentation and PR descriptions that other teams depend on
Authorized to work in the United States, and able to be based in Miami

Nice to have, and genuinely not required:

An internship or co-op where you shipped a data pipeline or report to production
Experience with a BI tool (Looker, Tableau, Power BI) or building a dashboard someone other than you used
Exposure to AWS or another cloud provider
Familiarity with relational or document databases (PostgreSQL, MongoDB)
Anything you’ve built on top of LLM or agent APIs - tools, harnesses, evals, agents
Curiosity about healthcare data standards (HL7, FHIR, DICOM) or claims/eligibility data - we’ll teach you these, and we’d rather you question how things are done in healthcare than arrive already knowing
Coursework or projects involving statistics, data modeling, or data warehousing concepts

What we'll give you

A published career framework with written promotion criteria, so you can see the path from Associate Software Engineer through Senior, Staff and Principal, and know exactly what's expected at each step. A mentor from among our senior engineers, for whom mentorship is a written part of their job. Real ownership, quickly. And a mission that's easy to get behind with real life impact.

The base salary range for this position is $85,000 - $115,000. Individual compensation will depend on various factors, including qualifications, skills, experience, location, and applicable laws. In addition to base salary, this role is eligible to participate in our equity incentive and competitive benefits plans.

Fraud and Security Notice:

Please be aware of recent job scam attempts. Our team uses the oneimaging.com email domain exclusively. If you have been contacted by someone claiming to be a OneImaging recruiter or a hiring manager from a different domain about a potential job, please report it to law enforcement here and to candidateprotection@oneimaging.com.

Equal Employment Opportunity:

OneImaging is proud to be an Equal Employment Opportunity employer and values diversity in the workplace. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views, or other applicable legally protected characteristics.

OneImaging is committed to providing accommodations for qualified individuals with disabilities in our recruiting process. If you need assistance or an accommodation due to a disability, you may contact us at talent@oneimaging.com.

Apply nowOpens OneImaging’s application page

About this role

From OneImaging’s careers page.

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
Ask why. We reason from first principles and we have an explicit norm that engineers are not implementation machines - if a requirement doesn’t make sense, we want you to say so
Handle protected health information correctly, with data governance, access controls, and audit logging as first-class requirements rather than afterthoughts

About you:

Graduating with a B.S. or M.S. in Computer Science, Data Science, Computer Engineering, or a related technical discipline between December 2026 and June 2027
You’ve built things nobody assigned you - side projects, coursework you took further than required, hackathon work, something with real data, however small
Strong SQL skills and working knowledge of Python for data processing
Some exposure to Databricks, Spark, or a similar distributed data processing tool - coursework, an internship, or a personal project is enough; we don’t expect production experience
A basic mental model of how data moves from a source system into a warehouse or lakehouse and out to a report
You use AI coding tools and you’ve formed opinions about them - including where they mislead you and how you catch it
You can explain a technical decision you made and what you’d do differently, which matters more to us than the sophistication of the project
Comfortable with ambiguity and with being told “we haven’t figured that out yet”
Intellectually honest: you can change your mind when the evidence changes, and you’d rather delete your own work than defend it
Clear written and verbal communication - you’ll be writing documentation and PR descriptions that other teams depend on
Authorized to work in the United States, and able to be based in Miami

Nice to have, and genuinely not required:

An internship or co-op where you shipped a data pipeline or report to production
Experience with a BI tool (Looker, Tableau, Power BI) or building a dashboard someone other than you used
Exposure to AWS or another cloud provider
Familiarity with relational or document databases (PostgreSQL, MongoDB)
Anything you’ve built on top of LLM or agent APIs - tools, harnesses, evals, agents
Curiosity about healthcare data standards (HL7, FHIR, DICOM) or claims/eligibility data - we’ll teach you these, and we’d rather you question how things are done in healthcare than arrive already knowing
Coursework or projects involving statistics, data modeling, or data warehousing concepts