Position: Data QA Engineer
Company: PSR company
Category: QA Automation
Experience required: 3y
English level: upper
Published: 2020-12-01T00:00:00+02:00

Необходимые навыки
• 3+ years of experience in Software development as Automation QA / SDET
• Strong prooved experience building complex e2e solutions from scratch
• Ability to analyze and troubleshoot complex data-based testing scenarios
• Familiarity with cloud-based / micro-services architecture

More about you
• Good level of English
• Willingness to learn and open mind about new technologies
• Confident to operate in a fast-paced environment
• A collaborative approach and willingness to engage in an environment of active idea sharing
• Ability to learn autonomously
• Excellent all-round communications skills

Будет плюсом
• Experience with any messaging system
• k8s experience
• SDET experience desirable

Предлагаем
• We offer a competitive financial package which includes competitive salary and quarterly bonus scheme
• We have a positive attitude to flexible working, a competitive annual holiday allowance, cycle to work scheme and supportive family polices
• State of the art, cool, centrally located offices with warm atmosphere, which creates good
working conditions
• Opportunity to travel to client offices based in London
• We have a culture of which we are proud, a highly skilled and diverse workforce as well as impressive offices in central London and Kiev

Обязанности
What you will be responsible for
Primarily we are looking for somebody to manage from design to execution the testing phase related to all time-series streaming data pipelines:
• Define acceptance criteria
• Prepare test data
• Designing and develop tests, mocks and stubs
• CI/CD pipeline building
• Test results analysis
This is a hands-on position for an expert QA engineer. In addition to practical coding and QA skills, an important aspect is played by soft skills tasks such as:
• Researching, gathering, organizing tests around data
• Evangelizing the importance of testing with real-world data to strength the system
• Enhancing a cultural shift in intensive data applications development cycle