Senior QA Analyst Cybersecurity Data & Databricks Testing
About The Position
The Senior QA Analyst supports enterprise cybersecurity data warehouse and dashboard solutions within a cybersecurity data operations function at a major global financial institution. The team works in an Agile environment and collaborates across data engineering, cybersecurity, development, and analytics functions. The role focuses on ensuring data platforms, security analytics, and reporting solutions provide dependable information to business and technology stakeholders. The position leads QA efforts across enterprise data platforms, including Databricks and cloud-based data environments. It develops and executes test strategies and automated data-validation solutions, validates data pipelines and transformations, tests REST APIs, manages defects, and maintains QA documentation and requirements traceability. The role also contributes to improved testing processes, automation practices, and QA standards. This is a W2-only opportunity (no C2C/1099) with a hybrid work arrangement in Charlotte, North Carolina.
Requirements
- 8+ years of experience in quality assurance, data testing, ETL/ELT testing, data engineering, or a closely related discipline.
- 5+ years leading QA initiatives involving enterprise data warehouses, data lakes, or lakehouse environments.
- Strong hands-on experience with Databricks and testing data pipelines within cloud-based data platforms.
- Advanced SQL and Spark SQL capabilities, including complex data validation, reconciliation, and troubleshooting.
- Hands-on programming experience with Python, PySpark, and Pandas for automation, profiling, analysis, and data-quality validation.
- Demonstrated experience testing ETL/ELT pipelines, transformations, and source-to-target mappings.
- Hands-on experience validating REST APIs, preferably with Postman or a similar tool.
- Experience with functional, integration, regression, system, performance, and user acceptance testing.
- Strong defect-management, documentation, and requirements-traceability skills.
- Ability to collaborate effectively with engineers, developers, cybersecurity stakeholders, and Agile delivery teams.
- Strong analytical and root-cause problem-solving capabilities.
Responsibilities
- Lead quality assurance efforts supporting enterprise cybersecurity data warehouse and dashboard solutions.
- Develop test strategies, plans, cases, and scripts based on business and technical requirements.
- Validate ETL/ELT pipelines, data transformations, and source-to-target mappings.
- Perform functional, integration, regression, system, performance, and user acceptance testing.
- Use SQL and Spark SQL for data reconciliation, validation, and root-cause analysis.
- Build and execute automated data-validation solutions using Python, PySpark, and Pandas.
- Test REST APIs using Postman or comparable API-testing technologies.
- Identify, document, prioritize, and track defects while partnering with developers through resolution.
- Maintain requirement-to-test traceability and supporting QA documentation.
- Participate in Agile ceremonies and provide feedback on system usability, data reliability, and platform stability.
- Improve testing processes, automation practices, and QA standards across cybersecurity data initiatives.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
