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YayPay is a fast-growing company with offices in New York, London, and an engineering team in Ukraine (Kyiv, Dnipro).
1 апреля 2021

Manual QA Engineer

Киев, Днепр, удаленно

Необходимые навыки

2+ years experience in manual testing (web-testing)
Theoretical knowledge base in software testing
Experience in creation different kinds of test documentation
Understanding REST
Knowledge in SQL
Understanding of Git
Understanding in CI (TeamCity, Jenkins)
Strong written and verbal communication skills in English (intermediate)

Предлагаем

Flexible working hours
A comfortable office in Kyiv with all the standard supplies(or you can work remotely)
A high-level (A1) corporate insurance from Uniqa
Tax compensation
Equipment (laptops, screens etc.)
Educational and professional development support

Обязанности

Collaborate in a cross-functional product team which is building friendly
Contribute to the improvement of our overall QA best practices.

О проекте

YayPay is building a cutting-edge accounts receivable management software that uses machine learning to help finance teams become revenue heroes. YayPay’s vision to help finance teams perform their most valuable work. We’re a rapidly growing company at the forefront of back-office automation, AI, and machine learning. YayPay is also one of the leaders of the industry in terms of user experience and consumerization of enterprise software.

From the technology perspective, YayPay Platform is a SaaS offering, which integrates with a number of different systems, such as:
— ERP systems to pull accounts receivable data from (e.g. NetSuite, Intacct, Sage X3 etc.)
— CRM systems, like SalesForce to pull and push relevant customer information
— Payment Providers to allow CreditCard and ACH to be made through the platform
— Credit Providers like CreditSafe to pull credit information

The application currently undergoes the phase of the active new feature development — we are working on building new modules: Reporting & Analytics Module, Credit Module, Cash Application Module.

The application is built on Service-Oriented Architecture, with the use of Kubernetes and technologies around it.

The main technology stack is described below:
— Back-End: Java 11, Spring Framework, Hibernate, MySQL, Kafka, Exasol
— Front-End: VueJS and KendoUI
— Machine Learning: Python and relevant machine learning libraries are used for the ML services
— Hosting: the application is hosted on AWS, with extensive use of the native AWS services

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