Mustafa Agarli

Mustafa Agarli

Qa Engineer @ Fannie Mae

About Mustafa Agarli

Mustafa Agarli is a QA Engineer at Fannie Mae in Washington DCWW with a background in Electrical and Electronics Engineering from Taiwan University of Science and Technology.

Title

Mustafa Agarli currently holds the position of QA Engineer at Fannie Mae in Washington DCWW. His role involves ensuring the quality and reliability of software applications through comprehensive testing frameworks and methodologies.

Current Position at Fannie Mae

Mustafa Agarli works as a QA Engineer at Fannie Mae, headquartered in Washington DCWW. His responsibilities include developing and executing automated regression suites to streamline testing processes and improve software quality. His work has led to significant reductions in testing time and improvements in overall system performance.

Previous Experience at City National Bank

Prior to his role at Fannie Mae, Mustafa Agarli was a QA Analyst at City National Bank in Los Angeles, California. During his six-month tenure from 2017 to 2018, he focused on validating functionalities across multiple modules, achieving a high bug detection rate and enhancing the reliability of software applications.

Education and Expertise

Mustafa Agarli holds a Bachelor's degree in Electrical and Electronics Engineering from Taiwan University of Science and Technology, where he studied from 2013 to 2017. His expertise includes using Java, Selenium, TestNG, and Cucumber for automating regression suites, as well as developing high-level frameworks that integrate with Jenkins and Jira.

Technical Contributions and Achievements

Mustafa Agarli has made notable technical contributions in his field. He automated regression suites using Java, Selenium, TestNG, and Cucumber, reducing testing time by 40%. He also validated various functionalities, achieving a 95% bug detection rate. Additionally, he developed a high-level automation testing framework, resulting in a 50% reduction in testing time. His implementation of a continuous integration and delivery pipeline using Jenkins and Git led to a 60% reduction in testing time. He conducted load and performance testing with JMeter, increasing system performance by 30%.

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