ETL Tester / Data Quality Engineer

About the Role

We seek a seasoned ETL Tester / Data Quality Engineer to ensure the integrity and accuracy of data integration, transformation, migration, and reporting activities within enterprise data systems. This role involves comprehensive validation across source systems, ETL workflows, data warehouses, data lakes, and reporting tools.

Key Responsibilities

• Interpret business requirements, analyze data mappings, and understand source-to-target transformations and rules.
• Create and execute test cases for ETL processes and data validation.
• Verify data consistency and completeness during its journey from sources through staging and transformation layers to targets.
• Perform reconciliation between source and target datasets to ensure data accuracy.
• Validate ETL transformation logic, including business rules, aggregations, calculations, and mappings.
• Conduct database testing utilizing advanced SQL queries.
• Test various data load methods such as incremental, full, historical, and batch loads.
• Assess dimensions of data quality like completeness, accuracy, consistency, uniqueness, validity, and integrity.
• Detect and report data anomalies such as duplicates, missing records, corruption, or wrongful transformations.
• Validate data migration and perform reconciliations between legacy and new systems.
• Assess ETL job robustness regarding error handling, restart/recovery mechanisms, scheduling, dependencies, and exceptions.
• Conduct regression testing after modifications to ETL pipelines or data models.
• Validate reports and dashboards against source databases or data warehouses for accuracy.
• Log and track defects until resolution through proper defect management practices.
• Collaborate closely with Data Engineers, Developers, Business Analysts, BI teams, and QA personnel.
• Support automation for repetitive validation and reconciliation tasks.
• Prepare detailed test documentation including plans, execution results, defect logs, and completion summaries.

Required Qualifications and Skills

• Hands-on experience in ETL and Data Warehouse testing environments.
• Proficient in SQL with deep knowledge of joins, subqueries, aggregations, common table expressions (CTEs), and reconciliation queries.
• Strong grasp of ETL concepts, data pipelines, data warehousing, and dimensional data modeling.
• Experience with databases like Oracle, SQL Server, PostgreSQL, MySQL, or equivalents.
• Familiarity with ETL tools such as Informatica, Talend, SSIS, IBM DataStage, Azure Data Factory, AWS Glue, or similar.
• Understanding of Data Lake, Data Warehouse, and Big Data architectures.
• Experience validating various data sources including APIs, flat files, CSV, JSON, and XML.
• Knowledge of data quality standards and data governance principles.
• Experience with defect and test management tools such as Jira, Azure DevOps, or similar platforms.

Preferred Skills

• Experience with cloud data platforms like Snowflake, Databricks, AWS, Azure, or Google Cloud.
• Ability to use Python for data validation and automation of tests.
• Familiarity with automated ETL and data testing frameworks.
• Knowledge of BI and reporting tools including Power BI, Tableau, or equivalents.
• Experience working in Agile or Scrum development environments.
• Exposure to Continuous Integration/Continuous Deployment (CI/CD) and automated quality gates for data pipelines.

Educational and Experience Requirements

• Bachelor's degree in Computer Science, Information Technology, Software Engineering, or related disciplines.
• At least three years of relevant experience within ETL, database, or data testing roles.
• Strong analytical thinking and problem-solving capabilities.
• Effective communication skills with the ability to work collaboratively across technical and business teams.

Success Criteria

The ideal candidate will independently validate complex data flows, accurately identify data quality issues, perform full end-to-end reconciliation, and guarantee that data delivered to downstream systems and users is complete, consistent, reliable, and accurate.