Senior Data Engineer

Atlas Medical Data Group; United States; Remote; USD 110,000 - 170,000; Full time

Job summary

Atlas Medical Data Group is seeking a hands-on data engineer to own and extend the Azure data warehouse for ABES and future practices. You will learn the current model, add integrations, and build transformations across clients, sessions, authorizations, claims, payments, staff, hours, and pay.

You will automate manual steps, deliver gross profit reporting and payroll-book reconciliation, and feed ERPNext while supporting the year-end close.

Qualifications

• Hands-on data engineer with cloud infra experience on Azure/AWS/GCP.
• Strong SQL and dimensional modeling for finance/operations use.
• Python for integration with SaaS and line-of-business systems.
• Experience building a data platform end-to-end in production.
• Familiar with healthcare data, HIPAA, and ERPNext data feeds.

Responsibilities

• Pick up the warehouse as it stands, learn how it was built, and take ownership.
• Extend integrations and add new ones, starting with banking APIs/exports.
• Build transformation layers and models (clients, sessions, authorizations, claims, payments, staff, hours, pay).
• Deliver gross profit reporting and payroll/billed services reconciliation.
• Feed ERPNext and support year-end close; automate manual steps.
• Implement data quality checks and build documentation for trusted numbers.

Skills

SQL & dimensional modeling

Python for integration

Cloud infrastructure (Azure/AWS/GCP)

Data warehousing design

HIPAA/Healthcare data knowledge

Education

Bachelor's degree in a relevant field

Tools

ERPNext

Azure Container Apps

Snowflake

Databricks

Microsoft Fabric

Job description

We are a founder-owned portfolio of healthcare businesses. The anchor is a healthcare price intelligence company that processes the price transparency files insurers are required to publish. These files disclose the rates they have negotiated with providers but are so massive and messy that almost no one can use them. We build the technology to turn the raw data into price intelligence, which has powerful applications across the US healthcare landscape.

One of the first applications is in care delivery. The data shows us which clinics are leaving money on their commercial contracts. We buy or partner with those clinics, help them close the gap, and run their back office through our management services organization. This year we acquired the first one, a multi-site autism therapy (ABA) practice.

About the engagement

We are looking for a data engineer to pick up and extend the Azure data warehouse behind ABES, an ABA therapy practice with two clinics in Illinois, and the management services organization (MSO) that will provide ABES and future practices with their non-clinical operations. The warehouse is up and its main sources are loaded. The work now is taking ownership of it, extending it, and making it something the finance team can rely on. The work sits with the operations and finance team and connects the systems the practice runs on today to the reporting and accounting that depend on them.

This is a contract engagement to start, and we want someone who can begin soon. The length is open, and as the portfolio grows there is more data work ahead, including on the price intelligence side.

Why this engagement exists

ABES is moving its accounting off QuickBooks and onto ERPNext. The warehouse needs to feed ERPNext with clean, reconciled data and support the year-end close. Gross profit and the tie-out between payroll and billed services both take manual work across several systems today. We want them to come from the warehouse. The MSO will serve more than one practice, so the data model has to anticipate more than one organization.

What you will do

• Pick up the warehouse as it stands, learn how it was built, and take ownership of it.
• Extend the integrations already in place and add new ones, starting with banking. Some systems offer APIs and some only offer exports.
• Build out the transformation layers and the models the business runs on, including clients, sessions, authorizations, claims and payments, staff, hours, and pay.
• Deliver gross profit reporting and a reconciliation between payroll and billed services.
• Feed ERPNext the data the books need, build report delivery inside ERPNext where it fits, and support the move off QuickBooks and the year-end close.
• Find the manual steps between the source systems, the warehouse and the books, and automate them.
• Build data quality checks and documentation so the finance team can trust the numbers without rechecking them.
• Help make platform decisions. Microsoft Fabric, Snowflake, and Databricks are under evaluation, and transformation tooling is still open.
• Use AI developer tooling as a normal part of how you build.

Who we are looking for

• A hands-on data engineer with cloud infrastructure experience on any of the major clouds (Azure, AWS or GCP), including setting up and deploying your own resources.
• Strong SQL and dimensional modeling. You have designed warehouses that finance or operations teams rely on.
• Strong Python for integration work. You have pulled data from SaaS and line-of-business systems through APIs and exports, handled different formats and authentication, and built it so the next source is easy to add.
• Has built and run a data platform end to end and supported it in production.
• Experience with finance data (general ledger, close, ERP, reconciliation) or healthcare data (claims, revenue cycle, HIPAA). Both is ideal.
• Works well with ambiguity. Can take a business question from a finance or operations lead and turn it into a data model and a working report.
• Comfortable working remotely with a small, distributed team and communicating clearly in writing.

What the engagement offers

• Your work gets used right away. The numbers you build will be used to run the business and close the books.
• The warehouse is young, so your design choices still shape it.
• Room to grow with the work. As the portfolio adds practices, the data platform has to scale with it.

What is hard about it

• Messy sources. Several of the practice's systems are poor and will not be replaced soon. Exports, inconsistent identifiers, and manual workarounds come with the work.
• Healthcare. The data includes protected health information, and HIPAA shapes how it is stored and accessed.
• Small team. You will be the data engineer, working with our technical lead, with no larger data team behind you.
• Ambiguity. Requirements come from finance and operations people describing their work. Part of the job is turning that into specs yourself.

Technical environment

• Data warehouse on Azure. Multi-organization support is still to be designed.
• ERPNext as the ERP and finance platform, replacing QuickBooks.
• Applications deployed on Azure Container Apps.
• Existing code is largely Python.
• Microsoft Fabric, Snowflake, and Databricks under evaluation for the warehouse platform.
• AI developer tooling (Claude Code or equivalent) in daily use.

Logistics

• Location: remote, US-based.
• Engagement type: contract, starting as soon as possible. Length open, with the potential to continue.
• Must be authorized to work in the US without sponsorship.