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MDaudit is seeking a Data Engineer, Onboarding to build and maintain data pipelines that ingest healthcare data (837, 835, EMR) into the platform, enabling revenue cycle and compliance initiatives. You will work closely with Implementation, Product, Support, and IT to onboard data efficiently and ensure onboarding projects stay on track.
The role emphasizes hands-on engineering with Databricks, PySpark, Python, and Snowflake.
Most job postings are the same (and can be pretty boring, right?!). That's why we want to start out by telling you what's in it for you:
The Data Engineer, Onboarding builds and maintains data pipelines that bring customer healthcare data, including 837 (claims), 835 (remittance), and EMR data, into the MDaudit platform and its analytic and operational applications that support revenue cycle and compliance initiatives. This is an internal engineering role that partners closely with Implementation, Product, Support, and IT teams to onboard customer data quickly and keep onboarding projects on track.
The role centers on hands-on engineering with a modern cloud data stack: Databricks, PySpark, Python, and Snowflake. The Data Engineer, Onboarding also supports converting data from legacy systems, builds automation to reduce manual onboarding effort, and monitors and maintains customer data feeds under guidance from senior engineers. The ideal candidate brings strong healthcare revenue cycle management (RCM) knowledge, including healthcare billing, the claims lifecycle, and reimbursement, along with working knowledge of healthcare EDI and electronic medical record systems.
Requirements
Essential Duties and Responsibilities Include but are not limited to the following:
Required Skills
Education and Experience
$125,000 - $135,000
Notice of AI Use in Job Application Review
As part of our commitment in creating a fair, efficient, and consistent hiring process we may use artificial intelligence (AI) to help our recruiting teams organize, summarize, and analyze information provided by candidates, including resumes, application responses, and other materials submitted during the application process.AI may be used to identify patterns, highlight relevant skills, and experience, and assist in comparing a candidate’s qualifications with the requirement of a specific role. These tools are to improve efficiency and consistency while supporting more informed hiring decisions, which will ultimately be made by the hiring team.