Data & Integration Engineer

Role overview

Zyter is hiring a Data & Integration Engineer to connect an agentic AI platform to the clinical, administrative, and operational data of a large integrated healthcare system.

In this role, you will build secure data pipelines that provide AI systems with the right records, maintain data lineage, and ensure outputs can be traced back to their original sources.

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, including alerts, results, orders, consults, appointments, and notes, into a common model that AI agents and retrieval services can use.
• Prepare unstructured documents for retrieval through 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 electronic health record (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 service blueprinting use cases.
• Work with client IT teams and other contractors on interface agreements, access requests, and connectivity.

Protect and trace data

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

Deliver with the team

• Deliver work in two-week Agile sprints with weekly releases, using continuous integration and continuous delivery (CI/CD) and automated testing for pipelines and transformations.
• Track work, requirements, and tests in Jira and Confluence.
• Provide production support for data issues and develop 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 working with healthcare data.
• Hands-on experience with HL7 v2 and FHIR, as well as clinical data such as results, orders, encounters, and appointments.
• Strong SQL and Python skills, plus experience with ETL/ELT tools and workflow orchestration platforms such as Airflow.
• Experience building data pipelines on AWS, including services such as S3, Glue, Lambda, and 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.
• U.S. work authorization and residence in the United States.

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, including document parsing, embeddings, vector databases, and retrieval pipelines.
• Familiarity with healthcare terminologies and data models, including LOINC, SNOMED CT, ICD-10, CPT, and OMOP.
• Experience with streaming tools such as Kafka or Kinesis and container technologies such as Docker and Kubernetes.