Healthcare data engineering faces challenges no other industry shares: EHR systems that resist data extraction (proprietary formats, limited APIs until FHIR), clinical data standards (HL7 v2, FHIR R4, USCDI, ICD-10, CPT, SNOMED CT) that require specialized mapping, HIPAA compliance on every data flow, and the data quality requirements where an incorrect lab result isn't just a data quality issue — it's a patient safety issue.
Healthcare data engineering requires: EHR integration expertise (Epic Clarity/Caboodle, Cerner HealtheDataLab, FHIR R4 APIs), clinical terminology mapping (ICD-10, CPT, SNOMED, RxNorm), HIPAA-compliant infrastructure (encryption, access controls, audit trails, BAAs), and the data quality frameworks appropriate for clinical data where accuracy is a safety requirement.