Lead Data Engineer (Healthcare Interoperability)

TL;DR

Lead Data Engineer (Healthcare Interoperability): Designing and maintaining Azure-based data infrastructure for healthcare data exchange with an accent on EHR integration and compliance standards like FHIR and HL7. Focus on building scalable data pipelines, optimizing database performance, and providing technical leadership to the engineering team.

Salary: $140,000–$160,000

Company

hirify.global is a healthcare technology company focused on interoperability and secure data exchange solutions.

What you will do

• Design and implement secure, scalable data architectures on Azure.
• Build and maintain complex ETL/ELT pipelines and event-driven data processing solutions.
• Optimize database performance, indexing, and query execution across multiple platforms.
• Integrate with external REST APIs and develop internal data APIs using Python.
• Provide technical mentorship to junior engineers and contribute to architecture reviews.
• Ensure data integrity and compliance with HIPAA/HITRUST requirements.

Requirements

• 8+ years of experience in data engineering or database development.
• Expert-level proficiency in T-SQL, Microsoft SQL Server, and Python.
• Strong experience with Azure data services including Data Factory, Synapse, and Blob Storage.
• Solid understanding of database design, normalization, and data modeling.
• Experience with CI/CD practices, version control, and Infrastructure as Code.
• Excellent communication skills and ability to work in a collaborative team environment.

Nice to have

• Practical experience with FHIR resources and C-CDA document parsing.
• Experience integrating with EHR/EMR systems like Epic or Cerner.
• Knowledge of HL7 v2 message flows and parsing.
• Experience with AI development tooling such as GitHub Copilot.
• Understanding of HIPAA/HITRUST compliance in regulated industries.

Culture & Benefits

• Opportunity to work on critical healthcare interoperability challenges.
• Technical leadership role with mentorship responsibilities.
• Exposure to advanced Azure data and AI services.
• Collaborative environment with cross-functional teams.
• Focus on high-quality engineering standards and data governance.