QA Engineer – ETL & HL7 (Data Pipeline QA)

Location: Remote – India (UK Working Hours)

Job Type: Full-Time

Company: BigRio

About BigRio:

BigRio is a remote-based, technology consulting firm headquartered in Boston, MA. We specialize in delivering advanced software solutions that include custom development, cloud data platforms, AI/ML integrations, and data analytics. With a diverse portfolio of clients across industries such as healthcare, biotech, fintech, and more, BigRio offers the opportunity to work on cutting-edge projects with a team of top-tier professionals.

Job 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.

Key Responsibilities:

• 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.

Required Qualifications:

• 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.