Principal QA Engineer

Required Skills & Experience

Must-Haves:\n\t• 8 to 10+ years of software quality-engineering experience in enterprise SaaS environments\n\t• Principal-level ownership mentality, including independently driving defects through resolution and taking accountability for overall product quality\n\t• Advanced hands-on SQL skills for database-level validation, including row counts, field-level accuracy, aggregation logic, relational integrity, and source-to-report reconciliation\n\t• Experience testing reporting or business-intelligence systems and validating report output, analytical query results, and data transformations against source data\n\t• Strong manual testing expertise, including independently developing test strategies, test plans, test cases, and coverage across functional and non-functional scenarios\n\t• Experience validating complex datasets, calculations, null handling, boundaries, hierarchical data traversal, rollups, and report aggregations\n\t• Experience using AI tools for test-plan generation, test-case development, edge-case identification, security scenarios, or test-data creation\n\t• Proficiency in C# and hands-on experience with .NET test frameworks such as NUnit, xUnit, or MSTest\n\t• Proven ability to develop and maintain automated test suites\n\t• Experience with SQL-based data-validation automation and API testing\n\t• Knowledge of security-testing practices, including input validation, authentication and authorization boundaries, injection risks, and data-exposure vulnerabilities\n\t• Familiarity with OWASP principles and security tools such as Burp Suite or comparable platforms\n\t• Experience with JIRA and Xray for defect tracking, test management, tagging, execution tracking, and result publishing\n\t• Experience serving as an embedded QA engineer within an Agile or Scrum delivery team\n\t• Experience participating in sprint planning, refinement, standups, demos, and retrospectives\n\t• Strong written and verbal communication skills, including the ability to document defects with precise SQL evidence\n\t• Experience working with globally distributed teams across multiple time zones\n\t• Bachelor’s degree in Computer Science, Engineering, or equivalent professional experience

Nice to Have Skills & Experience

Plusses:\n\t• Background in financial reporting, equity compensation, financial services, or another regulated environment where accuracy and auditability are critical\n\t• Direct experience with Logi Analytics or Logi Symphony\n\t• Deep Oracle SQL and PL/SQL knowledge, including stored procedures, packages, views, execution plans, and query-performance tuning\n\t• Experience validating hierarchical or tree-structured data models and parent-child relationships\n\t• Familiarity with Power BI, Tableau, Cognos, or similar enterprise BI tools\n\t• Knowledge of Oracle performance and read-optimization capabilities, including materialized views, result cache, and analytical functions\n\t• Experience using Datadog or similar logging and observability platforms to troubleshoot test failures\n\t• Experience with Azure DevOps Pipelines, CI/CD test execution, and environment management\n\t• Familiarity with Azure SQL, Azure Analysis Services, or related Azure data services\nExperience with Playwright, Cypress, k6, SpecFlow, or similar modern testing tools

Job Description

Insight Global is seeking a Principal Quality Engineer, Reporting/BI Engineering for a top enterprise financial-software client. This hands-on individual contributor will serve as the primary quality owner for a Scrum team building sophisticated financial-reporting and business-intelligence capabilities for a strategic Fortune 100 engagement. Unlike a traditional application-focused QA position, this role centers on SQL correctness, source-to-report data accuracy, financial calculations, query performance, hierarchical data validation, and report-output fidelity. The engineer will combine advanced manual testing with SQL-based validation, API automation, C#/.NET test development, security testing, and AI-augmented quality practices. The ideal candidate is a highly accountable quality leader who can independently uncover complex data issues, provide precise technical evidence, and drive defects through complete resolution.\n\nDay-to-Day:\n\t• Serve as the primary quality voice embedded within a Reporting/BI Scrum team\n\t• Own quality from initial requirements review through production release\n\t• Ensure reporting changes have adequate functional, data-accuracy, performance, security, regression, and non-functional test coverage\n\t• Define, document, and execute test plans and test cases for reporting features, SQL changes, BI enhancements, and defect corrections\n\t• Identify positive, negative, boundary, null-handling, aggregation, hierarchical-traversal, and performance test scenarios\n\t• Write Oracle SQL and PL/SQL queries to reconcile report results with source data\n\t• Validate row counts, field-level values, financial calculations, aggregations, referential integrity, and report totals\n\t• Test stored procedures, packages, views, and query modifications for correctness, performance, and unintended downstream effects\n\t• Investigate data discrepancies and provide engineers with SQL evidence that isolates failures within the data pipeline\n\t• Validate query-performance benchmarks and identify regressions in report responsiveness\n\t• Test report formatting, filtering, totals, drill-down behavior, parameter handling, data binding, conditional logic, and exported output\n\t• Validate Logi Analytics or Logi Symphony reports and dashboards against underlying source data\n\t• Test financial-reporting output for accuracy, traceability, and auditability\n\t• Build and maintain automated test suites using C# and .NET testing frameworks\n\t• Prioritize SQL-based validation automation and API coverage, with UI automation as a secondary focus\n\t• Contribute reusable SQL assertion patterns, API tests, and automation capabilities to the shared testing framework\n\t• Execute automated tests in Azure DevOps CI/CD pipelines and distinguish genuine defects from environmental failures\n\t• Incorporate authentication, authorization, injection, input-validation, and data-exposure testing into normal QA coverage\n\t• Use AI tools to expand test coverage, author SQL validation queries, generate test data, and identify security or edge-case scenarios\n\t• Log, track, communicate, and own defects through resolution rather than stopping after initial identification\n\t• Participate in planning, refinement, standups, demos, and retrospectives\n\t• Partner with engineers, Product Management, the Principal QA Lead, and QA leadership to improve quality and testability\n\t• Communicate testing status, defect evidence, data findings, and release risks clearly\n\t• Interface with client stakeholders as needed to clarify reporting issues and document defect evidence\n\t• Operate as a 100% hands-on individual contributor with no direct reports