Quality Analyst

Quality Assurance Analyst – Enterprise Data Warehouse Position Summary The Quality Assurance (QA) Analyst is responsible for validating the quality, accuracy, completeness, and reliability of data and application changes within an Enterprise Data Warehouse (EDW) environment. The role focuses heavily on ETL and data validation, including source-to-target testing, data reconciliation, regression testing, and verification of reporting and analytics outputs. The QA Analyst works closely with business analysts, data architects, ETL developers, reporting developers, production support teams, and other technical resources to ensure that system changes meet business and technical requirements before deployment to production. Key Responsibilities Develop and execute test plans, test scenarios, test cases, and test scripts for EDW change requests, enhancements, defect fixes, and releases. Perform end-to-end testing of ETL processes, including validation from source systems through staging, operational data stores, dimensional models, fact tables, and reporting layers. Validate source-to-target mappings and confirm that transformation and business rules are implemented correctly. Perform data reconciliation using SQL to compare source and target record counts, totals, key data elements, and transformation results. Validate data completeness, accuracy, consistency, referential integrity, and duplicate handling. Perform functional, integration, system, regression, and production-validation testing. Test Informatica workflows, mappings, sessions, dependencies, and batch-processing results. Validate database changes, including tables, views, stored procedures, indexes, and data-model modifications. Verify reporting and analytics outputs in tools such as Cognos and Tableau against underlying EDW data. Develop reusable regression test suites for critical EDW processing. Identify, document, and track defects through resolution and retesting. Provide clear evidence supporting test results and release readiness. Participate in requirements and technical-design reviews to identify testability issues and potential defects early in the development lifecycle. Work with development teams to perform root-cause analysis of data discrepancies and processing failures. Support User Acceptance Testing (UAT) by assisting business users with test scenarios, test data, and defect analysis. Participate in release-readiness reviews and provide QA status, outstanding defects, risks, and recommendations. Perform post-deployment validation following production releases. Maintain QA documentation and testing evidence in accordance with project and client standards. Required Qualifications 5+ years of experience in software quality assurance, data warehouse testing, ETL testing, or a related technical role. Strong experience testing enterprise data warehouse and data-integration solutions. Advanced SQL skills with the ability to independently query and analyze large datasets. Experience validating ETL transformations and source-to-target mappings. Experience performing data reconciliation and identifying discrepancies across multiple data sources. Understanding of dimensional data models, fact and dimension tables, relational databases, and data warehousing concepts. Experience with ETL tools such as Informatica PowerCenter or comparable technologies. Experience with Oracle or other enterprise relational database platforms. Experience developing and executing regression, integration, and end-to-end test scenarios. Experience documenting and managing defects using tools such as Azure DevOps, Jira, or similar platforms. Ability to analyze complex data issues and distinguish data-quality problems from application, ETL, configuration, and source-system defects. Strong written and verbal communication skills. Preferred Qualifications Experience supporting Medicaid, healthcare, government, or other large-scale data warehouse environments. Experience testing Medicaid claims, member, provider, encounter, eligibility, or financial data. Experience with Azure data services, including Azure Data Factory and Azure Data Lake Storage. Experience validating Cognos, Tableau, or similar business-intelligence reporting solutions. Experience with Informatica PowerCenter. Familiarity with data-governance and metadata-management concepts and tools. Experience working in environments with formal change management, release management, and production-support processes. Experience with automated data-validation or regression-testing frameworks. Key Competencies The successful candidate should be highly analytical and comfortable investigating complex data discrepancies rather than simply executing predefined test scripts. The position requires the ability to understand data flows across multiple systems, independently develop SQL validation queries, trace data through ETL processes, and clearly document whether expected business rules have been implemented correctly. The QA Analyst should also be capable of assessing testing risk and determining where additional validation is necessary based on the scope and potential production impact of a change.