Middle Data Quality Engineer / Business Analyst

Location: Remote

Company

hirify.global is delivering a data modernization project for an American insurance company undergoing digital transformation.

What you will do

• Prepare test scenarios and detailed test cases for migrated data and transformations.
• Validate Bronze-layer data against source systems and perform source-to-target reconciliation across Bronze, Silver, and Gold layers.
• Check record counts, field values, transformations, duplicates, completeness, and other data quality dimensions.
• Investigate discrepancies and determine whether they originate in source data, transformation logic, or target systems.
• Define validation rules and acceptance criteria, maintain test evidence, and update technical and testing documentation.
• Collaborate with Data Engineers and technical leads on requirements, defect analysis, retesting, and regression testing.

Requirements

• 3+ years of hands-on experience in data quality assurance, data QA, ETL testing, or data testing.
• Strong SQL skills, including writing and optimizing queries for validation and reconciliation.
• Experience with data migration testing, ETL/ELT testing, source-to-target validation, and field-level reconciliation.
• Experience creating and executing test cases and scenarios and documenting technical findings.
• Ability to analyze large, complex datasets, diagnose discrepancies, work independently, and communicate issues effectively.
• Good English communication skills for documentation and stakeholder interaction.

Nice to have

• Exposure to Azure Synapse Analytics and Azure Data Factory.
• Basic understanding of PySpark testing, data lake, and lakehouse solutions.
• Familiarity with SQL Server, Azure SQL, and medallion data architectures.

Culture & Benefits

• Remote work within a collaborative data engineering environment.
• Close cooperation with Data Engineers and the Lead Data Engineer.
• Opportunity to contribute to the migration and modernization of a legacy data platform.