Maxim Taran
Senior Quality Engineer at National Payment Card System
Moscow, Moscow City, Russia
Summary
👤
Senior🎓
Top SchoolMaxim Taran is a Senior Quality Engineer with 11+ years sharpening test automation, performance testing and QA leadership across finance, cybersecurity and healthcare tooling, currently ensuring reliability at the National Payment Card System in Moscow. He builds end-to-end automation frameworks, leads test teams, and has driven load-testing platforms and internal apps to run performance suites—combining hands-on scripting with product-level communication. An active contributor to the JVM open-source datafaker project, he has improved locale-aware data generation and test coverage, showing attention to data quality and internationalization. Trained originally in biological sciences and later in systems programming, Maxim brings a rare blend of scientific rigor and systems-level engineering to complex testing problems.
11 years of coding experience
10 years of employment as a software developer
системное программирование, системное программирование at Университет Российской академии образованияЗооинженер, biology,genetic,chemistry,agriculture, Зооинженер, biology,genetic,chemistry,agriculture at Российский Государственный Аграрный Университет — Московская Сельскохозяйственная Академия им. К. А. Тимирязева
Английский
Github Skills (6)
unit-testing10
javas10
faker10
java10
testing10
regex9
Programming languages (12)
Github contributions (5)
datafaker-net/datafaker
Apr 2020 - Nov 2021
Generating fake data for the JVM (Java, Kotlin, Groovy) has never been easier!
Role in this project:
Back-end Developer & QA Engineer
Back-end Developer & QA EngineerContributions:10 commits, 3 comments, 2 issues in 1 year 6 months
Contributions summary:Maxim primarily contributed to the improvement and testing of the datafaker-net/datafaker project. Their work involved implementing locale-specific latitude and longitude generation, fixing regular expressions within tests, and refactoring the code by removing a variable. They also added tests and corrected existing ones to ensure the accuracy of the generated data. These changes focused on enhancing the localization capabilities and ensuring data quality within the library.
groovyjavajvmkotlintesting
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