Data Engineer (Implementation & Integration)

Company: Meduit

Location: United States (Remote)

Salary: $80,000 - $95,000 a year

Type: Full-time

Remote: Yes

Posted: 2026-08-14

About this role

About Us:

Meduit is a national leader in healthcare revenue cycle management, supporting hospitals and physician practices in 48 states. We focus on optimizing payments, allowing clients to focus on patient care, and pride ourselves on our core values: Integrity, Teamwork, Continuous Improvement, Client-Focused, and Results-Oriented. Learn more at www.meduitrcm.com.

About the Role:

The Data Implementation Engineer is responsible for designing, developing, and maintaining data integration solutions that implement client data from hospital systems into Meduit platforms, including data warehouses, mapping tools, payment portals, and collections systems. This role leverages Python, SQL, ETL technologies, and data modeling expertise to transform, validate, and optimize data workflows. The Data Implementation Engineer partners with Operations, Workflow, Technical Support, and Account Management teams to support client implementations, scalable data architecture, and ongoing data quality across systems.

Title: Data Implementation Engineer

Location: Remote United States

Schedule: Full-time

Department: Product Implementation

Compensation: $80,000 – $95,000

Key Responsibilities:

  • Develop and maintain Python-based scripts, utilities, and automation solutions to support data integration, transformation, validation, and reporting
  • Design, develop, and maintain logical and physical data models that support scalable data integration and reporting requirements
  • Analyze source system data structures and translate business requirements into efficient data models and database schemas
  • Build, optimize, and troubleshoot complex SQL queries and data transformation processes
  • Configure and maintain ETL processes across multiple structured and unstructured data sources
  • Support data warehouse development and ongoing improvements to data architecture and performance
  • Ensure ongoing data integrity, quality, and governance across ...

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