QA Engineer – ETL
4 days ago
- Role Overview
We are seeking a highly skilled QA Engineer with strong expertise in ETL and Data Engineering testing to ensure the quality, accuracy, and reliability of enterprise data pipelines and reporting solutions. The role involves validating data workflows, transformation logic, and reporting systems across multiple ETL tools and databases.
### Key Responsibilities
- Design, develop, and execute comprehensive test plans, test cases, and test scripts for ETL processes and data workflows.
- Perform data validation, reconciliation, and transformation testing across source, staging, and target systems.
- Validate ETL workflows built using DataStage, Business Object Data Services (BODS), and SQL Server Integration Services (SSIS).
- Collaborate with developers, data engineers, and business analysts to ensure data quality and accuracy across systems.
- Conduct SQL-based testing for data profiling, validation, and business logic verification.
- Perform defect reporting, root cause analysis, and regression testing.
- Support automation of ETL testing using SQL queries, scripts, or specialized tools.
- Work with large datasets to identify anomalies, gaps, and ensure compliance with business rules and performance requirements.
### Required Skills & Qualifications
- 4–8 years of experience in ETL/Data Warehouse/Data Engineering testing.
- Strong expertise in ETL tools such as IBM DataStage, SAP BODS, and/or SQL Server Integration Services (SSIS).
- Proficiency in SQL (writing complex queries, joins, aggregations, data validation).
- Experience in data warehouse concepts, data modeling, and reporting systems.
- Hands-on experience in data quality, data reconciliation, and transformation testing.
- Strong analytical skills to validate source-to-target mapping (STTM).
- Familiarity with BI tools (Tableau, Power BI, Business Objects) is a plus.
- Knowledge of automation frameworks for ETL testing is desirable.
- Excellent communication and problem-solving skills.
### Nice-to-Have Skills
- Experience with cloud data platforms (Azure Data Factory, AWS Glue, GCP BigQuery).
- Exposure to test automation frameworks for data pipelines (e.g., PyTest, Selenium with DB, QuerySurge, Informatica DVO).
- Knowledge of Agile/Scrum methodologies.
### Education
- Bachelor's or Master's degree in Computer Science, Information Technology, or related field.
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