Position: Manual QA
Company: sparkybit.com
Experience required: 2y
Category: QA
English level: intermediate
Published: 2021-08-01T00:00:00+03:00

What knowledge and experience we expect from our candidate:

- At least 2 years of practical quality assurance experience
- Ability to write QA documentation — test cases, checklists, test plans
- Experience with cross-browser/cross-platform testing
- Experience with bug tracking systems and test management tools
- English level — from intermediate and higher

Will be a plus:

- Knowledge of REST API testing
- Experience with AWS
- Experience with MongoDB, PostgreSQL

Responsibilities:

- Test execution – manual running of test cases, exploratory and ad-hoc testing without test cases based on own experience
- Requirements analysis (user stories, mockups)
- Planning, monitoring, and control of QC activities
- Close work with the dev team and business

In addition to interesting tasks, we also offer:

- Work as a PE (the company has an accountant who deals with these
questions), tax compensation
- 18 working days of paid vacation, 5 days of sick leave
- Cozy office in the city center, partial remote option
- A fully equipped workplace in the office with a partial remote working option
- Professional growth
- Access to internal English courses; 50% compensation of individual courses
- Participation in conferences and educational events, with compensation from 50% to 100% of the cost
- Social corporate activities and events

About client:

Our client is a market-leading, independent, pension data and administration systems consultant. Based in London, Guildford, and Edinburgh. The main business areas are:

- UK’s pension administration software packages
- Bespoke pension administration systems build and implementation management
- Data risk auditing and data migration
- Third-party pension administration outsourcing advice

About project:

We develop a solution that consists of independent components (subsystems) that cover different areas of processing and analysis of pension data, identity verification, big data processing using machine learning, etc.