QA Engineer

1 week ago


Noida, India Sonata Software Full time

Job Description Summary We are hiring a meticulous and skilled QA Engineer with expertise in data validation, report testing, and automation. The ideal candidate will have hands-on experience testing data pipelines, Power BI dashboards, and automated data workflows, ensuring end-to-end data quality and report accuracy. Key Responsibilities - Design and execute test strategies for ETL pipelines, data transformations, and BI dashboards. - Conduct manual and automated testing for data pipelines and reports. - Validate Power BI dashboards and reports for data correctness, layout integrity, and performance. - Automate data validations using SQL and Python (e.g., with PyTest, dbt tests, or custom scripts). - Perform cross-system data comparisons to ensure consistency across data layers and reports. - Collaborate with data engineers and analysts to understand business logic and ensure test coverage. - Maintain test documentation, including test plans, cases, and defect logs (e.g., in Jira). - Participate in agile sprints, release planning, and code reviews to embed QA early in the cycle. Qualifications - Bachelor's degree in information technology or related field; or an equivalent combination of education and experience sufficient to successfully perform the key accountabilities of the job required. - Exposure to Power BI DAX expressions and filters for deeper validation. - Experience with API testing tools (e.g., Postman, REST Assured). - Background in BI regression testing and automated report verification. - Familiarity with cloud platforms like AWS, Azure, or GCP. Experience - 3–6 years in QA roles, with focus on data engineering and reporting environments. - Proficiency in SQL for querying and validating large datasets. - Experience testing Power BI reports and dashboards (or similar tools like Tableau/Looker). - Experience with test automation frameworks (e.g., PyTest, Selenium, dbt tests). - Familiarity with ETL tools, Airflow, and data warehouses like Snowflake or BigQuery. - Understanding data quality concepts: completeness, accuracy, consistency, freshness. - Experience with version control (Git), CI/CD pipelines, and issue tracking (e.g., Jira).


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