Data Engineer with HL7 or FHIR / healthcare data experience

About Layer Health: Layer Health is a healthcare AI company spun out of MIT and backed by GV (Google Ventures), Define Ventures, Flare Capital Partners, General Catalyst, MultiCare Health System and Froedtert Health. We are solving the information problem in healthcare by building an AI layer that can accurately and scalably synthesize information from medical records. Our mission is to reduce friction everywhere in healthcare through our LLM-powered platform that solves chart review once and for all, across use cases.

We are looking for a Data Engineer with HL7 or FHIR healthcare data experience to join our engineering team in Boston or NYC (hybrid). This role requires a minimum of 6 years of work experience and involves building and maintaining robust data infrastructure that powers our AI-driven healthcare solutions.

Key Responsibilities:

• Design and implement data solutions for healthcare data processing and integration
• Work with HL7 and FHIR standards to process and transform medical data
• Develop and maintain data pipelines for healthcare data ingestion and transformation
• Collaborate with clinical teams to understand data requirements and use cases
• Ensure data quality, accuracy, and compliance with healthcare regulations
• Work with healthcare data standards and terminology systems
• Participate in architecture discussions and technical planning
• Develop and maintain data documentation and standards
• Troubleshoot and resolve data-related issues in production
• Mentor junior team members and share best practices
• Stay current with healthcare data standards and evolving requirements

Required Skills and Qualifications:

• Minimum of 6 years of professional software engineering experience
• Strong expertise in healthcare data processing and standards
• Experience with HL7 and FHIR standards for healthcare data exchange
• Proficiency in Python and/or other data processing languages
• Understanding of healthcare data formats and structures
• Experience with healthcare data warehouses and data lakes
• Knowledge of healthcare regulatory requirements and compliance (HIPAA, etc.)
• Strong SQL skills and experience with relational databases
• Understanding of healthcare data governance and privacy requirements
• Experience with cloud platforms (GCP, AWS, Azure)
• Familiarity with containerization technologies (Docker, Kubernetes)
• Strong problem-solving abilities and attention to detail
• Excellent communication and collaboration skills
• Ability to work independently and in a team environment
• Experience with healthcare data and medical records processing
• Understanding of healthcare IT systems and workflows

What You’ll Bring:

• Proven track record of working with healthcare data standards and systems
• Strong understanding of HL7 and FHIR data formats and protocols
• Experience working with healthcare data warehouses and data lakes
• Knowledge of healthcare regulatory requirements and compliance
• Experience with healthcare IT systems and clinical workflows
• Strong analytical and troubleshooting capabilities
• Passion for applying technology to solve real-world healthcare challenges
• Experience with modern data stack technologies
• Ability to work effectively in cross-functional teams
• Commitment to data quality and regulatory compliance

Compensation: The estimated pay range for this role is $160,000 - $220,000 annually, with competitive equity options. The position offers comprehensive benefits including unlimited PTO, medical, dental, and vision coverage, disability insurance, and retirement plans.

Work Environment: This is a hybrid role with work locations in Boston or NYC offices (2-3 days per week in-office). The engineering team values collaboration, innovation, and making a meaningful impact in healthcare through technology. We operate with a high-velocity, low-ego culture that encourages learning and growth.

Join us in building the future of healthcare through artificial intelligence and machine learning. Our mission is to transform how healthcare data is processed and utilized to improve patient outcomes and reduce healthcare friction.