Staff Interoperability Engineer - Healthcare Data

b.well Connected Health is addressing the challenge of fragmented health data in healthcare. They are seeking a Staff Interoperability Engineer to design, build, and scale health data exchange solutions, ensuring secure and compliant data exchange for millions of patients.

Responsibilities:

• Design and implement real-time health data exchange solutions supporting millions of patient records
• Build Patient Access APIs, Provider Directory APIs, and Bulk FHIR APIs (CMS Interoperability Rule compliant)
• Develop connections to national networks (Carequality, CommonWell, eHealth Exchange, TEFCA)
• Create scalable data pipelines ingesting from EMRs, HIEs, labs, pharmacies, payers, wearables, and IoT devices
• Implement FHIR R4 and US Core Implementation Guide across all integration points
• Build real-time data pipeline infrastructure using Cloud and AI Native tools, Python, Spark and Kubernetes
• Develop custom FHIR resource mappings, transformations, and validation logic for non-standard data sources
• Build HL7 v2.x to FHIR conversion engines at scale
• CCDA conversions to FHIR
• Create automated testing frameworks for FHIR conformance, data quality, and integration validation
• Troubleshoot multi-system integration issues: data mapping conflicts, API failures, patient matching challenges, compliance gaps
• Implement SMART on FHIR authorization (OAuth 2.0, OpenID Connect, backend services)
• Build security controls: mTLS, JWT validation, API rate limiting, audit logging
• Maintain HIPAA, 21st Century Cures Act, and ONC certification compliance
• Implement consent management and granular data sharing controls
• Partner with product, clinical, and engineering teams to define interoperability requirements
• Create technical documentation: API specs, FHIR profiles, data mappings, troubleshooting guides
• Mentor junior engineers through code reviews and knowledge sharing
• Stay current with emerging healthcare interoperability standards and regulations

Requirements:

• 6+ years in healthcare interoperability or health IT
• 4+ years designing and implementing FHIR-based solutions (FHIR R4 required)
• Proven track record building production health data exchange for Millions of patients
• Extensive experience with 5+ EMR platforms (Epic, Cerner, Allscripts, athenahealth, eClinicalWorks, Meditech, NextGen)
• Production experience implementing Patient Access APIs or Bulk FHIR APIs (CMS Rule compliant)
• Production experience with HIE/HIN integrations and national networks (Carequality, CommonWell, eHealth Exchange, or TEFCA)
• Expert-level HL7 FHIR R4: resource models, profiles, extensions, search parameters, bulk data
• Deep understanding of US Core IG (v3.1.1+, v4.0+, v5.0+, v6.0+) and USCDI v1-v4
• Proficiency with SMART on FHIR (OAuth 2.0, OpenID Connect, SMART scopes, backend services)
• Strong knowledge of HL7 v2.x (ADT, ORM, ORU, SIU, MDM messages)
• Experience with CDA/C-CDA documents (parsing, validation, FHIR conversion)
• Understanding of clinical terminologies: SNOMED CT, LOINC, RxNorm, ICD-10, CPT, CVX
• Knowledge of ONC certification, CMS regulations, and 21st Century Cures Act
• Strong experience designing and building RESTful APIs and FHIR APIs at scale
• Proficiency with message queuing (Kafka, RabbitMQ, Event driven systems)
• Experience with API security: OAuth 2.0, JWT, mTLS, rate limiting
• Understanding of microservices, API gateways, and asynchronous processing patterns
• Experience with using AI tools and agents to accelerate engineering best practices & implementation
• Strong Python skills (required) plus one of: Java, JavaScript/TypeScript, Go, C#
• SQL and NoSQL databases: PostgreSQL, MySQL, MongoDB, DynamoDB, Redis
• Data formats: JSON, XML, FHIR JSON/XML, HL7 v2.x, CSV, Parquet
• Data validation: JSON Schema, FHIR Validator, Schematron
• Version control (Git), CI/CD pipelines, automated testing (pytest, JUnit, Jest)
• Distributed data processing: Apache Spark (PySpark, Spark SQL, Spark Streaming)
• Containerization: Docker and Kubernetes (Deployments, Services, Helm)
• Cloud platforms: AWS (preferred), Azure, or GCP
• Data pipeline patterns: ETL/ELT, streaming, batch processing, CDC
• Hands-on experience with FHIR servers
• FHIR validation tools: HL7 FHIR Validator, Inferno, Touchstone
• Custom FHIR profiles, extensions, and implementation guides
• Advanced Interoperability
• Patient matching algorithms, probabilistic matching, MPI systems
• Clinical data quality assessment, profiling, anomaly detection
• Consent management frameworks (FHIR Consent, XACML, DS4P)
• Payer data exchange: claims (837, 835), prior authorization, coverage determination
• Da Vinci Project: PDex, CDex, HRex, DTR, PAS
• Gravity Project: SDOH Clinical Care IG
• CARIN Blue Button for payer data access
• FHIR Questionnaire/QuestionnaireResponse for structured data capture
• Wearables/IoT: Apple HealthKit, Google Fit, Fitbit, FHIR Device/Observation
• Pharmacy: NCPDP SCRIPT, Surescripts integration
• Lab data: ORU/ORM messages, LOINC mapping, DiagnosticReport
• LLMs/AI for clinical data extraction, normalization, terminology mapping
• Open-source healthcare contributions (HAPI FHIR, Synthea, FHIR Converter)
• HL7 FHIR certification or HL7 working group participation