Experience:

<ul>
<li>3-6 years in QA roles, with focus on data engineering and reporting environments.</li>
</ul>

<ul>
<li>Proficiency in SQL for querying and validating large datasets.</li>
</ul>

<ul>
<li>Experience testing Power BI reports and dashboards (or similar tools like Tableau/Looker).</li>
</ul>

<ul>
<li>Experience with test automation frameworks (e.g. PyTest, Selenium, dbt tests).</li>
</ul>

<ul>
<li>Familiarity with ETL tools, Airflow, and data warehouses like Snowflake or BigQuery.</li>
</ul>

<ul>
<li>Understanding data quality concepts: completeness, accuracy, consistency, freshness.</li>
</ul>

<ul>
<li>Experience with version control (Git), CI/CD pipelines, and issue tracking (e.g. Jira).</li>
</ul>

Non-Technical Requirements:

<ul>
<li>Proven success in contributing to a team-oriented environment.</li>
</ul>

<ul>
<li>Strong analytical, problem-solving, and decision-making capabilities.</li>
</ul>

<ul>
<li>Excellent communication (written and oral) and interpersonal skills.</li>
</ul>

<ul>
<li>Self-driven and highly organized, with a proactive approach to operational excellence.</li>
</ul>

Qualifications:

<ul>
<li>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.</li>
</ul>

<ul>
<li>Exposure to Power BI DAX expressions and filters for deeper validation.</li>
</ul>

<ul>
<li>Experience with API testing tools (e.g., Postman, REST Assured).</li>
</ul>

<ul>
<li>Background in BI regression testing and automated report verification.</li>
</ul>

<ul>
<li>Familiarity with cloud platforms like AWS, Azure, or GCP.</li>
</ul>

Roles &amp; Responsibilities

<ul>
<li>Design and execute test strategies for ETL pipelines, data transformations, and BI dashboards.</li>
</ul>

<ul>
<li>Conduct manual and automated testing for data pipelines and reports.</li>
</ul>

<ul>
<li>Validate Power BI dashboards and reports for data correctness, layout integrity, and performance.</li>
</ul>

<ul>
<li>Automate data validations using SQL and Python (e.g. with PyTest, dbt tests, or custom scripts).</li>
</ul>

<ul>
<li>Perform cross-system data comparisons to ensure consistency across data layers and reports.</li>
</ul>

<ul>
<li>Collaborate with data engineers and analysts to understand business logic and ensure test coverage.</li>
</ul>

<ul>
<li>Maintain test documentation, including test plans, cases, and defect logs (e.g. in Jira).</li>
</ul>

<ul>
<li>Participate in agile sprints, release planning, and code reviews to embed QA early in the cycle.</li>
</ul>

QA Engineer

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. Roles &amp; 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.

QA Engineer in Apollo (UID-15883)

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Job Description for QA Engineer

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