QA Engineer

Role                       : QA Engineer

Location               : Seattle WA (Locals only)

 

We are seeking a highly skilled Data Migration Test Analyst to support enterprise data migration initiatives into Snowflake within an Azure ecosystem. This role will be responsible for validating the accuracy, completeness, integrity, and transformation of data as it moves from legacy platforms and data warehouses into modern cloud-based data environments.

The ideal candidate will have strong experience in expertise in data validation, ETL/ELT validation, source-to-target reconciliation, migration testing, , data quality testing, SQL analysis, enterprise reporting validation, and automated testing methodologies. Experience with Alteryx is highly preferred.

Key Responsibilities

• Design and execute end-to-end testing strategies for data migration and modernization initiatives.
• Validate data transformations, mappings, and business rules between source systems and Snowflake target environments.
• Perform source-to-target reconciliation testing to confirm completeness, accuracy, and consistency of migrated data.
• Develop and execute SQL-based validation scripts against large datasets.
• Create, execute, and maintain test cases, test plans, and detailed test evidence.
• Validate ETL/ELT pipelines and data ingestion processes.
• Develop automated data validation scripts and reusable testing frameworks.
• Investigate data anomalies, transformation issues, and reconciliation exceptions.
• Support functional, integration, regression, and user acceptance testing activities.
• Perform data profiling, data quality assessments, and root cause analysis.
• Collaborate with Data Engineers, Data Architects, Product Owners, and Business Analysts to resolve data quality issues.
• Develop data quality metrics and testing dashboards to measure migration success.
• Validate reporting and analytics outputs migrated from legacy platforms into Snowflake.
• Participate in Agile ceremonies including sprint planning, backlog refinement, and defect triage.
• Document defects with detailed root-cause analysis and testing results.

Required Qualifications

Data Testing & Quality

• 5+ years of experience in Data Warehouse, ETL, and/or Data Quality Testing.
• Strong experience validating enterprise data migration projects and cloud-based platforms.
• Experience performing source-to-target data validation and reconciliation testing.
• Hands-on experience creating test strategies, test plans, and traceability documentation.
• Experience supporting large-scale enterprise migration programs involving multiple source systems.
• Strong understanding of data quality frameworks and data governance concepts.

Technical Skills

• Strong SQL skills for data validation and analysis.
• Expertise in testing ETL/ELT pipelines.
• Hands-on experience with Snowflake.
• Experience working within Microsoft Azure data environments.
• Experience validating APIs and data integrations.
• Experience using Azure DevOps, Jira, or similar testing management tools.

 

Preferred Qualifications

• Alteryx Designer or Alteryx Server experience (Highly Preferred)
• Experience building automated data validation and reconciliation workflows in Alteryx.
• Experience with data profiling and data quality monitoring tools.
• Experience with QuerySurge or similar data comparison tools.
• Experience supporting Snowflake migration programs from legacy EDW, SQL Server, Teradata, or other enterprise platforms.
• Preferred experience within Financial Services, Banking, Lending, or Wealth Management environments.
• Basic Python scripting for data validation and testing automation.
• Experience validating Power BI datasets, semantic models, or Azure analytics solutions.

Desired Background

Candidates who have successfully:

• Tested large-scale migrations into Snowflake.
• Validated complex source-to-target mappings.
• Performed enterprise data reconciliation across millions of records.
• Supported cloud modernization programs leveraging Azure.
• Utilized Alteryx for data profiling, cleansing, transformation validation, and testing automation.