About The Role
We are looking for a QA Engineer to lead quality assurance activities across complex, multi-phase cloud data platform delivery. This role covers system and integration testing, parallel-run validation, UAT coordination, and regression testing across all data domains, dashboards, and exception management workflows - ensuring all deliverables meet accuracy thresholds and compliance sign-off requirements before production deployment.
Key Responsibilities
- Design and execute system and integration test plans covering data pipeline flows, transformation layers, evaluation engine outputs, and exception workflows
- Perform end-to-end pipeline validation across all data domains, verifying data quality gate pass rates and schema conformance
- Conduct parallel-run comparisons between automated system outputs and manual reference reports, targeting minimum 90% agreement thresholds
- Author UAT test scripts and coordinate sign-off across multiple stakeholder groups including operations, compliance, executive, and audit teams
- Validate dashboard accuracy against known control outcomes and verify KPI calculations across all reporting layers
- Verify exception and alert workflow behavior including automated ticket creation, SLA countdown triggers, and escalation patterns
- Log and manage defects in Azure DevOps, providing root-cause analysis for pipeline discrepancies and evaluation logic issues
- Support regression testing activities across all domains following each production deployment
- Conduct production smoke testing across all dashboards, pipelines, and integrations prior to formal go-live sign-off
- Collaborate with Data Engineers, Technical Leads, and business stakeholders throughout QA cycles
Required Skills & Experience
- 5+ years of experience in QA or testing roles within data platform, ETL, or cloud analytics projects
- Experience designing and executing test plans for data pipelines, including schema validation, transformation accuracy, and data quality checks
- Familiarity with Azure DevOps for test case management, defect logging, and release tracking
- Experience with parallel-run or reconciliation testing methodologies, comparing automated outputs against reference datasets
- Ability to interpret SQL query results and validate data transformation logic across layered data architectures
- Exposure to Power BI or BI dashboard validation including KPI accuracy checks and visual consistency reviews
- Understanding of UAT coordination processes and stakeholder sign-off workflows across persona groups
- Strong analytical skills with attention to detail and ability to identify root-cause discrepancies in complex data flows
- Good communication skills and ability to document findings clearly for both technical and business audiences
