Data Engineer

VetsEZ•Jackson, MS

1d•Remote

About The Position

VetsEZ is seeking a Data Engineer for a remote opportunity supporting the implementation and operation of a statewide Health Information Exchange (HIE) and the development of a Health Data Utility (HDU). The role builds healthcare data pipelines and owns terminology mapping, validation, and data quality remediation. The opportunity is contingent upon contract award. The candidate must reside within the continental United States. The successful candidate will build and maintain data pipelines and help ensure that healthcare data is accurately mapped, validated, reliable, recoverable, and securely handled. The role also involves documenting data lineage, terminology mappings, quality rules, and operational procedures for analytics-ready datasets.

Requirements

Bachelor’s degree in computer science, data engineering, health informatics, information systems, or a related field.
At least 5 years of relevant experience, with demonstrated experience across the stated responsibilities.
Experience building production data pipelines and healthcare or comparable regulated data solutions.
Strong SQL, data modeling, transformation, and pipeline troubleshooting skills.
Experience with clinical terminology mapping, reference data, and healthcare data validation.
Knowledge of standard vocabularies such as LOINC, SNOMED CT, ICD-10-CM, or RxNorm.
Ability to implement automated quality checks and resolve data discrepancies with clinical and technical stakeholders.
U.S. citizenship is required.
Selected candidates must successfully complete a background check.
Ability to obtain and maintain a Government/Public Trust clearance, including required fingerprinting, when required for the position.

Nice To Haves

Experience with HIE data, EHR extracts, laboratory feeds, or FHIR resources.
Experience with Azure data services, Python, or comparable engineering tools.
Health informatics or health information management credential.

Responsibilities

Build and maintain data ingestion, transformation, aggregation, and warehouse pipelines.
Map source clinical codes and local terminology to standard vocabularies and reference data.
Implement validation, reconciliation, and data quality monitoring within engineering workflows.
Investigate discrepancies and coordinate remediation with providers, clinical analysts, and integration teams.
Optimize pipeline performance, reliability, recoverability, and secure handling of sensitive health data.
Document lineage, terminology mappings, quality rules, and operational procedures for analytics-ready datasets.
Take on additional tasks and responsibilities as needed to support team objectives and ensure project success.