75% Remote: Data QA Engineer (f/m/d)

For our client we are looking for a Data QA Engineer (f/m/d).

Outline data:
Start: asap / 01.06.2024
Duration: 31.12.2024++
Workload: Full-time
Location: Berlin, 75% remote (3 weeks remote / 1 week Berlin), up to 50% onsite

Role:
The role of dedicated QA engineer in the Data tower within the project is crucial for increasing level of maturity for provided Data services. The QA engineer contributes to bring Data technologies user experience to
the new stage by ensuring its high quality, smooth maintenance and carefree allowing to focus just on usage them.

In this role, you will be responsible for test design, manual execution, and test automation for K8s operators that enable the efficient deployment, scaling, and management of data-related services and technologies within our Kubernetes infrastructure.

Targets:
- Requirements and dependencies analysis for Kubernetes (K8s) operators tailored for data technologies, including databases, data processing frameworks, and related tools.
- Close collaboration with Data dev team to understand implementation details, functionality, and planned scope.
- Test design (component/component integration tests) and manual execution where applicable.
- Tests automation to integrate test suites to automatic pipeline.
- Close collaboration with QA engineers of other teams to understand possible technical dependencies.
- QA/test scope estimation and planning.
- Regression testing and releases approval.

Skills (must-have):
- Strong experience in requirements analysis, test planning and test design, test reporting,
- Deep understanding of different types (functional, regression, security, availability, etc) and levels (component, integration, e2e) of testing,
- Experience with data technologies (PostgreSQL, Kafka, etc),
- API testing experience,
- Working experience with GitLab, understanding of CI/CD,
- Good understanding of K8s (containers/docker, helm),
- Strong user experience with Jira, Confluence, test management software,
- Ability to understand complex systems, abstract relevant information and communicate accordingly,
- Agile knowledge

Skills (should-have):
- Good experience with pytest,
- Experience with test automation framework implementation/adjustment,
- Experience with TestRail,
- Experience with infrastructure platform projects,
- Experience with GCP, Azure, AWS public clouds.