Qa Jobs 2026 (Now Hiring) – Smart Auto Apply

A global financial-services organization is seeking a senior QA Analyst to support a Cyber Data Operations team responsible for enterprise data platforms and analytical dashboards.This highly technical QA position will ensure the accuracy, reliability, and completeness of data moving through complex warehouse and cloud-based environments. The successful candidate will use SQL and Python-based tools to validate data, automate testing, investigate defects, and verify ETL/ELT transformations from source through target.This is not a traditional manual or UI-focused QA position. Candidates must be comfortable working directly with data and independently investigating why pipelines, transformations, or analytical outputs are incorrect.RESPONSIBILITIES

• Develop and execute detailed test plans, test cases, and test scripts
• Test enterprise data pipelines, transformations, dashboards, and related data products
• Validate ETL and ELT processing from source through target
• Perform complex data validation and reconciliation using SQL
• Use Python-based tools to automate testing, profiling, and quality checks
• Test data-warehouse, data-lake, lakehouse, and cloud-platform functionality
• Validate record counts, business rules, transformations, nulls, duplicates, and expected outputs
• Investigate discrepancies and perform root-cause analysis
• Identify, document, report, and track defects through resolution
• Build and maintain reusable automation and regression-test coverage
• Validate REST API behavior and resulting data
• Maintain traceability between requirements, test cases, defects, and final validation
• Perform functional, integration, regression, system, and user-acceptance testing
• Partner with engineers, developers, and stakeholders in an Agile/Scrum environment

Role Requirements:

• At least eight years of experience in QA, data testing, ETL/ELT testing, data engineering, or a related discipline
• Senior-level hands-on quality-assurance experience
• Advanced SQL for complex validation, reconciliation, and troubleshooting
• Hands-on Python experience for automation, analysis, or data validation
• Strong enterprise data-testing experience
• Experience testing ETL/ELT pipelines and data transformations
• Understanding of source-to-target mappings
• Experience testing data warehouses, data lakes, or lakehouse environments
• Experience building and maintaining regression-test coverage
• Functional, integration, system, regression, and UAT experience
• Strong defect-analysis and root-cause investigation skills
• Experience working within Agile/Scrum teams
• Ability to work onsite in Charlotte at least three days per week

PREFERRED EXPERIENCE

• Databricks
• Spark SQL
• PySpark or Pandas
• REST API testing with Postman or similar tools
• Collibra
• Cybersecurity or security-analytics data
• Cloud-based data-platform experience
• Python-based QA automation frameworks