Healthcare Interoperability & Clinical Data Specialist

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Healthcare Interoperability & Clinical Data Specialist based in the United States.

This role focuses on onboarding, transforming, validating, and supporting clinical data from diverse healthcare sources and interoperability partners.

You will work with healthcare data standards including CCD/C-CDA, HL7, FHIR, and REST APIs to make complex clinical information usable and reliable.

The position combines healthcare interoperability, data engineering, clinical data quality, analytics, and technical troubleshooting.

You will help integrate data from EHR vendors, health information exchanges, aggregators, and internal systems into scalable and normalized data models.

A key part of the role is assessing data quality, clinical usability, terminology, and suitability for quality measurement and analytics use cases.

You will collaborate across technical, clinical, and business teams to resolve integration challenges and establish reliable data pipelines.

This opportunity is well suited to an experienced healthcare data professional who enjoys working at the intersection of clinical information, interoperability standards, and data technology.

As a Healthcare Interoperability & Clinical Data Specialist, you will help bring new clinical data sources into production while ensuring that information is accurately interpreted, transformed, validated, documented, and fit for downstream use.

• Analyze and interpret clinical data from new and existing sources, with a focus on CCD/C-CDA documents, FHIR resources, HL7 messages, and API-based exchanges.
• Evaluate the structure, semantics, completeness, consistency, and clinical usability of data from EHRs, health information exchanges, aggregators, and other interoperability partners.
• Develop, enhance, and maintain processes for parsing, extracting, normalizing, transforming, and validating XML, JSON, delimited files, APIs, and other healthcare data formats.
• Map source data elements and clinical concepts to normalized internal models and, where applicable, FHIR resources and standard terminologies.
• Lead or support onboarding of new clinical data sources through source discovery, sample-file analysis, field and code mapping, profiling, validation, defect identification, and production-readiness assessment.
• Create automated data quality checks and reconciliation processes to identify missing sections, malformed documents, inconsistent coding, duplicate clinical facts, unexpected values, and source-specific anomalies.
• Investigate interoperability and integration issues, conduct root-cause analysis, and coordinate resolution with vendors, exchanges, aggregators, IT teams, and business stakeholders.
• Develop and maintain reusable Python and SQL utilities for data profiling, parsing, comparison, validation, exception handling, and large-scale analysis.
• Work with FHIR resources and RESTful APIs to retrieve, inspect, validate, and transform clinical data, including resource relationships, references, profiles, bundles, and terminology bindings.
• Analyze CCD/C-CDA documents at both document and section level, including templates, entries, identifiers, codes, dates, providers, encounters, observations, and procedures.
• Assess clinical data sources for downstream use cases such as quality measurement, supplemental data, clinical analytics, population health, and HEDIS reporting.
• Create and maintain source inventories, interface specifications, data dictionaries, mapping documents, validation rules, data lineage, known limitations, and onboarding procedures.
• Participate in user acceptance testing, production support, source certification, release…