quality engineer (manual)

Symfa provides custom software development and software services, including enterprise mobility, quality assurance, DevOps, blockchain development, machine learning, and backend development. The company also works on digital transformation, workflow automation, CRM and ERP software, eCommerce portals and marketplaces, data, and business intelligence. This project is for an American insurance company with over 40 years of experience in credit insurance.

• Prepare test scenarios and detailed test cases for migrated data and transformations;
• Validate Bronze-layer data against source systems for accuracy and completeness;
• Reconcile source and target data across Bronze, Silver, and Gold layers;
• Validate record counts, field values, transformations, duplicates, and data completeness;
• Investigate discrepancies between source and target systems;
• Define and implement validation rules and acceptance criteria for data migration;
• Maintain test evidence and document test results and findings;
• Prepare and update technical and testing documentation throughout the project lifecycle;
• Collaborate with Data Engineers and the Lead Data Engineer to clarify requirements and resolve technical issues;
• Participate in defect analysis, retesting, and regression testing as needed.

• 3+ Years of hands-on experience in data quality assurance, data QA, or ETL/data testing;
• Solid SQL knowledge and practical ability to write and optimize queries for data validation and reconciliation;
• Applied experience in data migration testing or ETL/ELT testing;
• Experience validating data between source and target systems;
• Exposure to data quality dimensions, including completeness, accuracy, consistency, uniqueness, and validity;
• Experience creating and executing test cases and test scenarios;
• Experience with data reconciliation, including comparing record counts and field-level data;
• Ability to investigate and diagnose discrepancies and distinguish issues in source data, transformation logic, or target systems;
• Strong attention to detail and ability to work effectively with large and complex datasets;
• Practical experience preparing and maintaining clear technical and testing documentation;
• Ability to work independently and communicate findings and issues effectively to developers and technical leads;
• Good English communication skills for documentation and stakeholder interaction;
• Nice to have: Exposure to Azure Synapse Analytics and Azure Data Factory, basic understanding of testing PySpark, data lake, and lakehouse solutions, familiarity with SQL Server and Azure SQL, awareness of Medallion data architectures.

• No conditions specified