QA Consultant - Data Testing | ETL | SQL | Cloud Data Platforms

QA Consultant - Data Testing | ETL | SQL | Cloud Data Platforms

remote only on w2 basis!

Job Summary

• We are seeking an experienced QA Consultant - Data Testing with strong expertise in validating enterprise data platforms, ETL pipelines, cloud data warehouses, and business intelligence solutions.
• The ideal candidate will possess hands-on experience in data quality assurance, SQL validation, ETL testing, data migration testing, API validation, and cloud-based data ecosystems .
• This role requires close collaboration with Data Engineers, Data Architects, Business Analysts, and Product Owners to ensure high-quality, reliable, and accurate data solutions.

Key Responsibilities

• Design, develop, and execute comprehensive test strategies for enterprise data platforms and analytics solutions.
• Validate ETL/ELT pipelines to ensure accurate extraction, transformation, and loading of data.
• Perform source-to-target data validation across multiple databases and cloud environments.
• Develop SQL queries for backend data validation, reconciliation, and integrity checks.
• Validate data migration projects involving structured and semi-structured data.
• Perform end-to-end testing of Data Warehouse and Data Lake solutions.
• Execute functional, regression, integration, system, and user acceptance testing for data applications.
• Validate reports, dashboards, KPIs, and analytical data delivered through BI platforms.
• Test batch processing, streaming data pipelines, and real-time integrations.
• Validate APIs supporting enterprise data ingestion and data services.
• Collaborate with Data Engineers to troubleshoot data quality and pipeline issues.
• Participate in Agile ceremonies including sprint planning, backlog refinement, stand-ups, and retrospectives.
• Create test plans, test cases, test scripts, and defect reports.
• Work closely with business users to validate business rules and reporting accuracy.
• Support production deployments and post-release validations.
• Drive continuous improvements in Data QA processes and automation.