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Senior Quality Assurance Engineer - DAX @ Datavail

INOnsiteFull-timeJob reference 1878
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About this role

Datavail is a leading provider of data management, application development, analytics, and cloud services, with more than 1,000 professionals helping clients build and manage applications and data via a world-class tech-enabled delivery platform and software solutions across all leading technologies. For more than 17 years, Datavail has worked with thousands of companies spanning different industries and sizes, and is an AWS Advanced Tier Consulting Partner, a Microsoft Solutions Partner for Data & AI and Digital & App Innovation (Azure), an Oracle Partner, and a MySQL Partner. Title: Senior Quality Assurance Engineer

Location: Hyderabad/Mumbai/Bangalore

Education: Bachelor’s Degree

Exp Level: 5+ Years

Job Description:

• Own and lead the entire QA function for the program. • Define and execute a two-pillar testing strategy: • Calculation Accuracy . • Validate DAX measures using known-answer testing • Leverage XMLA endpoints for automated validation • Ensure 100% match-to-expected outputs (“match-to-ship” standard) • Data Completeness & Security • Validate row-level data completeness • Test Row-Level Security (RLS) implementations in Power BI • Build and maintain automated QA test harnesses for semantic models. • Validate conformed dimensions and fact tables against source systems. • Drive reconciliation-to-the-penny validation in partnership with Finance stakeholders. • Derive test scenarios, fixtures, and expected outputs from legacy reporting systems. • Coordinate QA efforts through report build-out and reconciliation phases to project close.

Roles and Responsibilities:

• 5+ years of experience in Data/BI Quality Assurance or related roles. • Strong hands-on expertise in: DAX (Data Analysis Expressions) SQL • Experience testing Power BI semantic models and reports, including: Measures and calculations, Row-Level Security (RLS) • Proven experience building or operating automated test frameworks for data or BI systems. • Strong understanding of data validation, reconciliation, and QA methodologies.

Ability to interpret and validate outputs against legacy systems or reports.

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