QA Engineer

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).