Data & Integration Engineer - Healthcare - HL7/FHIR - Python - AWS

Data & Integration Engineer

Remote

Full Time

Role summary

Data & Integration Engineer to connect an agentic AI platform to the clinical, administrative and operational data of a large integrated healthcare system. You will build the secure pipelines that feed the AI the right records, keep track of where every data element came from, and make the outputs traceable back to source.

Key responsibilities

Build data pipelines

• Design and build batch pipelines, and near-real-time interfaces where approved, to ingest structured, semi-structured and unstructured data from client-designated sources.
• Normalize clinical data (alerts, results, orders, consults, appointments, notes) into a common model the AI agents and retrieval services can use.
• Prepare unstructured documents for retrieval: parsing, chunking, metadata tagging and loading into search or vector indexes.
• Build automated data quality checks, and monitor pipelines for failures, delays and schema changes.
• Define system and data flows, systems of record, interface contracts, security boundaries, error handling and reconciliation approaches.
• Translate client architecture requirements and constraints into actionable requirements for Zyter engineering teams.
• Partner with engineering teams on design decisions and review solutions for scalability, performance, reliability, security and maintainability.

Integrate with source systems

• Build and maintain interfaces to EHR and scheduling systems using HL7 v2, FHIR APIs, database extracts and flat files.
• Map data fields across systems and document them in data dictionaries and system/data maps, including for the service blueprinting use case.
• Work with the client's IT teams and other contractors on interface agreements, access requests and connectivity.

Protect and trace the data

• Maintain data lineage and provenance so every AI output links back to the exact source record.
• Apply role-based access, encryption in transit and at rest, audit logging and retention controls for protected health information.
• Support security reviews and authorization packages with data flow diagrams and interface documentation.

Deliver with the team

• Ship in two-week Agile sprints with weekly releases, using CI/CD and automated tests for pipelines and transformations.
• Track work, requirements and tests in Jira and Confluence.
• Provide production support for data issues, and write runbooks and technical documentation for handover.

Required qualifications

• Bachelor's degree in computer science, information systems, engineering or a related field, or equivalent experience.
• 6+ years of data engineering or integration experience, including 3+ years with healthcare data.
• Hands-on experience with HL7 v2 and FHIR, and with clinical data such as results, orders, encounters and appointments.
• Strong SQL and Python, plus experience with ETL/ELT tools and workflow orchestration (such as Airflow).
• Experience building data pipelines on AWS (such as S3, Glue, Lambda, RDS) with CI/CD and automated testing.
• Experience with data quality checks, data lineage and metadata management.
• Working knowledge of HIPAA and secure handling of protected health information.
• US work authorization and residence in the US.

Preferred qualifications

• Experience with integration engines such as InterSystems HealthShare / IRIS, Mirth Connect or Rhapsody.
• Experience integrating with Epic, Oracle Health or another major EHR.
• Experience preparing data for AI: document parsing, embeddings, vector databases and retrieval pipelines.
• Familiarity with healthcare terminologies and data models: LOINC, SNOMED CT, ICD-10, CPT, OMOP.
• Experience with streaming tools (such as Kafka or Kinesis) and containers (Docker, Kubernetes).