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.

Required Skills:

QA EngineeringData