ETL QA Automation Engineer, IQVIA

• To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below represent the knowledge, skill, and ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions
• Bachelor’s degree in Computer Science, Information Systems, or equivalent practical experience
• Advanced expertise in SQL with strong understanding of relational data models and database structures
• 4+ years of experience defining, executing, and automating QA test cases with an ETL focus
• 4+ years of hands‑on testing experience with Talend or similar ETL / integration platforms
• Strong experience testing complex ETL transformations, mappings, and data pipelines
• Experience with AWS technologies including S3, Athena, Glue, and Redshift
• Proven ability to translate manual ETL validation efforts into scalable automated test solutions
• Strong analytical and troubleshooting skills with a focus on data integrity and root‑cause analysis
• Excellent organizational and time management skills with the ability to synthesize business and technical requirements
• Proficiency with flowcharting and process‑mapping tools such as Lucidchart or Visio
• Strong written and verbal communication skills with attention to detail
• Ability to work independently and collaboratively in cross‑functional Agile teams
• Experience working with Agile tools such as JIRA

Desirable

• The ETL QA Automation Engineer is responsible for hands-on testing, automation, and data validation across ETL pipelines, data integrations, and downstream applications
• This role leads the definition and execution of an automation testing strategy for ETL processes, ensuring data accuracy, integrity, and reliability across internal and third‑party data sources
• Working closely with distributed business and technical stakeholders, the ETL QA Automation Engineer identifies data quality issues, analyzes root causes, and drives corrective actions
• A successful candidate is motivated to define new QA processes and standards, challenge assumptions, and continuously improve testing practices to deliver high‑quality data products for customer
• Write complex SQL queries to validate ETL workflows, transformations, and output datasets
• Discover, troubleshoot, and resolve data quality issues and discrepancies across ETL processes
• Build, maintain, and continuously enhance an automated QA framework for ETL testing
• Define and maintain ETL test strategies, test plans, test cases, and validation documentation
• Monitor ingestion and transfer of data from internal and third‑party sources, ensuring accuracy and timeliness
• Validate complex ETL mappings, transformations, and data logic across environments
• Partner with engineering, product, and data teams to resolve ETL defects and support re‑testing
• Log, track, and manage ETL defects and enhancements using JIRA
• Document QA processes and recommend improvements to enhance testing efficiency and effectiveness
• Facilitate ETL deployments to QA environments and support release readiness activities
• Act as an ETL QA subject matter expert and mentor team members on data quality best practices
• Ensure data quality risks and deviations from specifications are escalated to management in a timely manner