Mirth Connect Developer

Start Date: 20/04/2026

End Date: 31/12/2026

Location: Zaventem (Hybrid)

We are looking for several talented and motivated Interface and Data Migration Analysts to join our team as part of a large-scale Epic implementation project in a hospital environment. In this role, you will work on designing and developing high-quality interface and data migration processes between hospital information systems. Collaboration, innovation, and attention to detail will be key in ensuring seamless interoperability and traceable data exchange that support patient care and operational efficiency.

Key Responsibilities:

• Design, develop, and maintain interfaces using Mirth Connect, ensuring compliance with healthcare standards (HL7 v2/v3, FHIR).

• Design and execute data migration and data transformation flows (clinical, administrative, and reference data).
• Analyze source systems, data models, and business rules to ensure accurate and consistent data mapping.
• Collaborate with cross-functional teams (IT, medical staff, administration, Epic analysts) to analyze requirements and implement integration solutions.
• Troubleshoot and resolve integration issues to guarantee system interoperability and performance.

Required Skills:

• Ability to understand business requirements.

• Ability to write formal functional and technical specifications.
• Ability to write clean, maintainable, and efficient integration code.
• Experience with data analysis, data mapping, and data quality controls.
• Proven experience with Mirth Connect or ETL tools.
• Java programming skills for custom scripting and connector development is an asset.
• Solid knowledge of SQL and relational databases.
• Knowledge of HL7 standards and healthcare interoperability protocols.
• Experience with Epic interfaces or data migration.

Preferred Qualifications:

• Bachelor's degree in Computer Science, Software Engineering, or a related field.

Skills:

• Business Requirements

• ETL
• Java
• Javascript
• Middleware
• RESTful API
• Soap API
• SQL