AM Level - Data QA KPMG Global Services

  • company name KPMG Global Services
  • working location Office Location
  • job type Full Time

Experience: 5 - 5 years required

Pay:

Salary Information not included

Type: Full Time

Location: Karnataka

Skills: Analytics, Data Transformation, Power Bi, Alteryx, SQL, Python, Data Testing, test strategy development, validation testing, Powerapps, azure data factory, Databricks, Azure Data Lake Storage, Azure SQL, Microsoft Fabric, User Acceptance Testing UAT, Collaboration Skills

About KPMG Global Services

Job Description

Senior Quality Assurance (QA) Engineer, Tax Technology Roles and responsibilities The responsibilities of the role include: Collaborate with stakeholders to gather data testing requirements and understand business needs. Lead, design and execute test plans for data pipelines, ETL processes, and analytics platforms. Validate data accuracy, integrity, and transformations across systems. Develop and maintain automated test scripts for data validation and reporting. Identify data quality issues, report defects, and verify fixes. Work in Agile teams, contributing to continuous improvement and best testing practices. Requirement Proven expertise in testing Data and Analytics components, with strong contributions to test strategy development. Skilled in data transformation and validation testing, ensuring data integrity through both manual and automated methods. Experience in testing Power BI dashboards and PowerApps, ensuring accuracy of metrics and visualizations. Hands-on experience in projects leveraging tools like Alteryx, Azure Data Factory, and programming languages such as SQL and Python. Familiar with modern data platforms and tools including Databricks, Azure Data Lake Storage (ADLS), Azure SQL, Microsoft Fabric, and PowerApps. Proficient in leading User Acceptance Testing (UAT) and coordinating with business users. Strong collaboration skills to resolve data-related technical issues and support data infrastructure requirements. Keeps up-to-date with emerging trends and technologies in the data and analytics space.,