EU remote
Senior IT Software Quality Engineer – Data & ETL ( M/F/H )
About this role
We are looking for an experienced IT Software Quality Engineer Data & ETL who will be responsible for leading and executing quality assurance activities within complex data platforms and cloud-based ecosystems. In this role, the focus is on ensuring the quality, accuracy, completeness and reliability of data across end-to-end data pipelines. You will work at the intersection of software testing, data engineering, ETL, Big Data and cloud technologies.
You are analytical, technically skilled and able to independently execute testing activities while coordinating effectively with developers, data engineers, business analysts, product owners and other stakeholders. The Role: As a Senior IT Software Quality Engineer Data & ETL, you will be responsible for planning, executing and continuously improving QA activities within data-intensive environments. You will test end-to-end data flows and ETL processes, ensuring that data is correctly extracted, transformed and loaded.
You will also validate data across different systems and identify deviations, inconsistencies and data quality issues. You combine hands-on testing with data analysis and work closely with both technical and business stakeholders. ETL & Data Validation: You will be responsible for: Performing end-to-end testing of ETL and data workflows Validating extraction, transformation and loading processes Performing data reconciliation and cross-system validation Checking data quality, completeness, consistency and accuracy Identifying and analyzing discrepancies between source and target systems Validating complex data transformations and business rules Test Planning & Execution: You will: Analyze business and technical requirements Develop detailed test scenarios and test cases Create comprehensive test strategies Perform functional, integration, system and regression testing Monitor test coverage and quality throughout releases Ensure a structured end-to-end testing lifecycle Identify quality risks at an early stage and propose solutions SQL & Data Analysis: An important part of the role is performing advanced data analysis.
You will: Use advanced SQL for data validation Validate complex joins, aggregations and transformations Verify business rules within datasets Analyze source-to-target mappings Investigate data-related defects and inconsistencies Use SQL to identify the root cause of data quality issues Test Automation: Where possible, you will contribute to further automation of data validation. You will preferably work with: Python PySpark Pandas You will develop and maintain reusable automation utilities and frameworks to improve the efficiency, reliability and scalability of the testing process.