> Markdown version of [/jobs/ext/3587145-etl-tester](https://www.wearedevelopers.com/jobs/ext/3587145-etl-tester). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # ETL Tester - **Company:** Indotronix Avani Group - **Location:** Columbus, OH, United States - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Amazon Web Services, Amazon S3, Automation of Tests, Microsoft Azure, Cloud Computing, Continuous Integration, Information Engineering, Extract Transform Load (ETL), Data Warehousing, IBM InfoSphere DataStage, Python (Programming Language), Cloud Services, Selenium, SQL Databases, Sql Optimization, Snowflake, Pytest, Data Analytics, Cucumber (Software) - **Published:** October 5, 2026 - **Apply:** https://candidateportal.ceipal.com/job-details/594EhihDV3DKMz8g-UNwanQTJsNXvgKBgTZ284U1uCI ## About the Role Bachelor's degree required. - Minimum 5 years' ETL testing experience in a data warehouse environment. - At least 3 years' test automation experience, including leadership of QA Analysts on teams. - Minimum 2 years' hands-on experience with Snowflake and AWS. - Strong proficiency with Azure DevOps, Python, AWS S3, Snowflake, Zena, and DataStage. Preferred Skills - Financial services or banking industry background. - Advanced SQL and data warehouse knowledge. - Hands-on with test automation tools: Cucumber, Selenium, PyTest, DBT tests. - Experience with cloud data platforms, especially Snowflake and AWS. - Familiarity with CI/CD tools (Azure DevOps). - Excellent communication, organizational, analytical, and problem-solving skills. - Highly motivated with strong attention to detail and ability to prioritize tasks., Education: A bachelor's degree is required Experience: Candidates must have at least 5 years of ETL testing experience in a data warehouse environment 3 years of test automation experience 2 years of experience with Snowflake and AWS and 2 years of experience leading QA Analysts on a project team Technical Skills: Key technologies include Azure DevOps Python AWS S3 Snowflake Zena and DataStage Preferred QualificationsExperience in the financial services or banking industryStrong experience with SQL ETL Testing and data warehouse conceptsProficiency in test automation tools such as Cucumber selenium PyTest or DBT testsExperience with cloud data platforms (Snowflake AWS)Familiarity with CI/CD tools such as Azure DevOpsExcellent verbal and written communications skillsAbility to effectively prioritize and execute tasksDetail-oriented and highly motivated with strong organizational analytical and problem-solving skills ## Description ETL Tester - Data QA Automation Lead (Onsite, 4 days/week - Columbus, OH | Minneapolis, MN | Dallas, TX), Join an innovative Data Lake and Data Warehouse team as an ETL Tester and QA Automation Lead. In this influential role, you'll develop robust test automation frameworks and quality assurance strategies to ensure enterprise data is accurate, reliable, and a true strategic asset. You will collaborate with cross-functional teams, drive continual process improvements, and play a key part in delivering data solutions that meet banking regulatory standards., Lead quality assurance efforts for data ingestion and integration projects, ensuring compliance with regulatory requirements. - Design, build, and maintain scalable automated testing frameworks and CI/CD pipelines. - Develop and execute comprehensive test strategies for System Integration Testing (SIT) and support User Acceptance Testing (UAT). - Collaborate with data engineers, developers, and project managers to ensure end-to-end data quality and traceability. - Drive continuous improvement of QA processes and methodologies. - Design and implement automation frameworks to optimize testing efficiency. - Generate daily and weekly test execution metrics and status reports. - Support project teams in defect resolution and actively participate in walkthroughs, inspections, and user group meetings. - Analyze data, troubleshoot issues, and develop action plans to resolve data quality concerns. - Oversee production implementation verification and validate system quality.