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# QA Engineer - ETL & HL7 (Data Pipeline QA) in , United States

- **Company:** Energy Jobline
- **Location:** Boston, MA, United States (Remote available)
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Amazon Web Services, Automation of Tests, Microsoft Azure, Big Data, Data Validation, Information Engineering, Data Integrity, Extract Transform Load (ETL), Data Mapping, Data Warehousing, Interoperability, Apache JMeter, Cloud Services, Selenium, Strategies of Testing, Freeform SQL, Fast Healthcare Interoperability Resources, Pytest, Health Level Seven International, Data Pipelines
- **Published:** October 17, 2026
- **Apply:** https://www.energyjobline.com/job/qa-engineer-etl-hl7-data-pipeline-qa-united-states-31981878

## About the Role

4+ years of experience in QA with a focus on ETL/data pipeline testing.
Hands-on experience with HL7 message formats and healthcare data exchange.
Strong understanding of data warehousing concepts, data mapping, and validation techniques.
Proficient in writing complex SQL queries for data validation.
Experience working with large datasets in a cloud or hybrid environment.
Familiarity with QA automation tools is a plus (e.g., PyTest, Selenium, JMeter).
Strong communication and documentation skills.
Nice to Have:
Experience with cloud data platforms like AWS, Azure, or GCP.
Prior experience in the healthcare or life sciences domain.
Knowledge of FHIR standards or healthcare interoperability.

QA Engineer - ETL & HL7 (Data Pipeline QA) in , United States

## Description

We are seeking a highly skilled and detail-oriented QA Engineer with strong experience in ETL testing and HL7 validation to join our growing data engineering team. This role will focus on data pipeline testing, ensuring data accuracy, quality, and integrity as it moves across systems and services in a healthcare-focused environment., Design, develop, and execute test plans and test cases for ETL processes and data pipelines.
Validate data transformations, data integrity, and completeness across source and target systems.
Conduct end-to-end testing of HL7 messages and healthcare data flows.
Collaborate with developers, data engineers, and stakeholders to define test strategies and identify issues.
Automate QA processes wherever feasible using appropriate scripting and tools.
Perform root cause analysis and ensure timely defect resolution.
Ensure compliance with data quality standards and healthcare regulations.