Full Stack QA Engineer (Python)

Andersen is hiring a Full Stack QA Engineer (Python) for a project enhancing data science solutions and ensuring the quality and performance of machine learning models. The customer is a global investment management firm providing tailored investment solutions to institutional and private clients. It combines financial expertise with long-term investment strategies to help clients achieve their objectives while adapting to changing market conditions. The organization focuses on innovation, responsible investing, and operational excellence, continuously enhancing its capabilities to deliver sustainable value and support long-term growth. The project is focused on developing and improving data science solutions that leverage numerical, textual, and visual data to deliver measurable value to users. It includes building and evaluating machine learning models, assessing their performance, and continuously optimizing their impact on products and user experience.

Responsibilities: - Actively participating in all stages of the product lifecycle, from initial concept through to deployment. - Testing backend services, analyzing results, and identifying issues. - Developing and maintaining test plans, test cases, and documentation for applications. - Writing API automated tests using Pytest or other relevant tools. - Identifying, documenting, and tracking bugs and issues using a bug tracking system. - Collaborating with cross-functional teams to understand project requirements and clarify ambiguities. - Performing regression testing to ensure product stability after new changes. - Collaborating with TechOps and other teams to implement quality management processes and improve testing.

Requirements: - Experience in QA, predominantly in backend testing, with strong proficiency in Python (Pytest) for writing and maintaining automated test scripts for 3+ years. - Proficient in working with Linux and related tools; solid knowledge of Bash scripting. - Understanding of Docker/Kubernetes principles, basic CI/CD knowledge, and the ability to analyse backend service logs, including using Open Lens or similar tools. - Experience with Kafka and Kibana or a willingness to quickly learn them. - Skilled in testing RESTful and gRPC APIs. - Basic proficiency in SQL. - Good understanding of client-server and/or microservice architecture. - Ability to work in a team. - Familiarity with the basics of Machine Learning - Level of English – from Intermediate+ and above.

Compensation: 2150–3350 EUR per month.