Atlas Systems - Quality Assurance Specialist - ETL/Datawarehouse Testing

Department Icon Data Science Analytics & Machine Learning
Posted: 1 month ago
0-1 years
Bengaluru / Bangalore, Karnataka
Data Science Analytics & Machine Learning
work from office
Full Time
Closes 16 Nov 2026

Posted: 1 month ago
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Job Description

About Us

Atlas Systems Inc. is a Software Solutions company headquartered in East Brunswick, NJ. Incorporated in 2003, Atlas provides a comprehensive range of solutions in the areas of GRC, Technology, Procurement, Healthcare Provider and Oracle to customers across the globe. Combining our unparalleled experience of over two decades in the software industry and global reach, we have grown with extensive capabilities across multiple industry verticals.

Quality Assurance (QA) Specialist Power BI / Microsoft Fabric :

Overview

We are seeking a detail-oriented QA Specialist with strong hands-on expertise in Power BI testing, Data Analytics QA, and Microsoft Fabric. The role focuses on ensuring data accuracy, reliability, usability, and performance across the analytics environment.

The ideal candidate should combine deep Power BI QA expertise with strong SQL, ETL, data validation, and Fabric knowledge, with the ability to trace issues end-to-end across data pipelines, Fabric data layers, semantic models, DAX, and Power BI reports.

Key Responsibilities

  • QA Strategy & Execution :
  • Develop QA strategies for Power BI reports, semantic models, ETL pipelines, and Fabric data workflows.
  • Define repeatable test cases and validation processes based on requirements, user stories, and acceptance criteria.
  • Perform functional, regression, integration, data migration, and UAT testing.
  • Power BI & Data Validation :
  • Test Power BI Service functionality including navigation, permissions, RLS, filters, slicers, drill-through, interactions, refresh, and usability.
  • Validate semantic models, relationships, measures, DAX logic, and filter context.
  • Reconcile Power BI outputs with SQL/Fabric backend data and validate business rules.
  • Perform root-cause analysis across source to ETL to Fabric to semantic model to DAX to visual.
  • Fabric / ETL Validation :
  • Validate Fabric pipelines, Lakehouse/Warehouse data, notebooks, and ETL/ELT transformations.
  • Perform source-to-target, reconciliation, completeness, accuracy, duplicate, null, aggregation, and business-rule validations.
  • Validate initial, incremental, and historical loads, including insert/update/delete scenarios.
  • Use SQL, PySpark/Spark SQL, and notebooks for large-scale validation where applicable.
  • Automation & Documentation:
  • Design reusable and automated validation frameworks for Power BI, data pipelines, models, and integrations.
  • Integrate validation into pipeline execution where appropriate.
  • Document test cases, validation results, defects, evidence, and QA metrics.
  • Support CI/CT and front-end automation using Playwright where applicable.
  • Collaboration & Issue Resolution:
  • Work with Business Analysts, Power BI Developers, Data Engineers, Data Modelers, and Governance teams.
  • Identify whether issues originate from data, transformation, pipeline, semantic model, DAX, or report/UI layers.
  • Drive defect investigation, RCA, UAT, production validation, and release readiness.

Required Skills & Experience

  • Strong hands-on experience in Power BI / Data Analytics QA.
  • Deep understanding of Power BI Service, DAX, semantic models, relationships, and report validation.
  • Strong SQL and backend data validation/reconciliation skills.
  • Strong understanding of ETL/ELT testing and data quality principles.
  • Hands-on or strong working knowledge of Microsoft Fabric and Azure data environments.
  • Experience with structured QA processes, test cases, defect management, and QA metrics.
  • Experience with automated testing/validation frameworks.
  • Strong documentation and troubleshooting skills.

Preferred Qualifications

  • Hands-on Fabric migration and data validation experience.
  • Fabric Notebooks, PySpark/Spark SQL, Databricks, ADF.
  • Reusable/config-driven data validation frameworks.
  • Playwright for Power BI/front-end testing.
  • XMLA, Semantic Link (SemPy), or semantic-model automation.
  • CI/CT, Azure security/governance, and AI testing frameworks.

(ref:hirist.tech)

Skills

Data AnalyticsData ValidationData MigrationDaxEtlQuality AssuranceAnalyticsAiSqlDatabricks

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