QA Engineer

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.

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).

Non-Technical Requirements:

• Proven success in contributing to a team-oriented environment.
• Strong analytical, problem-solving, and decision-making capabilities.
• Excellent communication (written and oral) and interpersonal skills.
• Self-driven and highly organized, with a proactive approach to operational excellence.

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.

• 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.