Position: Senior Manual QA engineer
Company: Geniusee
Experience required: 5y
English level: upper

Requirements

● 4+ years hands-on experience in QA Engineering
● Experience writing test plans, detailed test cases, and other formal test documentation
● Ability to troubleshoot and analyze issues to root cause, ideally at the code or log level
● Experience with web browser testing
● Hands on experience in testing APIs using tools like Postman
● Experience working in a CI/CD environment (like Jenkins, TeamCity, CircleCi, etc) for executing automated tests and scripts
● Upper-intermediate level of English (both written and spoken)

As a plus

● Experience with collaboration and productivity tools such as Confluence, JIRA and test case management tools (like TestRail, Xray/Zephyr for JIRA, etc.)
● Experience with version control systems like Git
● Experience with Chrome Dev Tools
● Strong motivation, high level of commitment, proactive and positive attitude
● Great problem solving skills and detail-oriented approach
● Excellent written and verbal communication skills

We offer

● Competitive salary level;
● English classes in the office;
● Exciting and challenging startup projects;
● Ability to practice English and communication skills through permanent interaction with clients from all over the world;
● Career development opportunity;
● Informal and friendly atmosphere;
● Cozy office near the city center;
● The ability to focus on your work: a lack of bureaucracy and micromanagement;
● Flexible working hours (start your day between 8:00 and 11:30);
● Team buildings, corporate parties;
● Paid vacation (18 working days) and sick leaves;
● Insurance;
● Unlimited work from home (remote).

Project: The platform for Revenue forecasting (USA). First Intelligent Revenue Management Platform built for the digital-selling and remote sales era. The platform solves the oldest problem in sales: the black box problem. The black box of Sales forecasting, pipelines, activity, and deals. Sales today operate on biased self-reported information and leaders are forced to use guesswork to make decisions causing forecasting slippage, lower win rates, inconsistent quota attainment, poor capacity allocation, and inefficient pipeline management.