QA AUTOMATION ENGINEER - SIMULATION ENGINES AND CLOUD SERVICES

• 50% Simulation Engines: Validating high-performance numerical software, scientific correctness, time-series datasets, and calculation performance.
• 50% Cloud Services & Platforms: Automating REST/gRPC APIs, integration workflows, and web services connected to scalable cloud infrastructure.

Working in an international, collaborative environment, you will work alongside software developers, scientists, and domain experts based across Berlin, Denmark, and the Czech Republic., * Framework Development: Design, build, and maintain scalable automated testing frameworks for simulation calculation engines and cloud platforms.

• Scientific Data & Output Validation: Develop automated regression suites to validate numerical calculations, time-series data, and output correctness against strict scientific tolerance criteria.
• Performance Benchmarking: Design and execute performance and benchmarking strategies from scratch to profile calculation speed, memory usage, and CPU multi-threading during heavy simulation runs.
• API & System Integration: Perform automated API testing (REST and gRPC) and conduct end-to-end integration testing across backend services.
• CI/CD Pipeline Integration: Integrate automated test suites into continuous delivery pipelines (e.g., GitHub Actions or TeamCity) running in containerized environments.
• Root-Cause Analysis: Investigate test failures across application code, simulation engines, compilers, dependencies, and configuration layers.
• Cross-Functional Collaboration: Partner effectively with remote software engineering and scientific teams to define quality criteria and expected test outcomes.

• Education: Bachelor’s or Master’s degree in Computer Science, Software Engineering, Information Technology, or a related field.
• Experience: Ideally 5 to 8 years of hands-on experience in Quality Engineering and Test Automation.
• Programming Skills: Strong proficiency in C# and Python for test framework development and scripting.
• Data & Backend Focus: Solid experience handling and asserting numerical outputs, time-series data, or large scientific datasets.
• API & UI Testing: Experience with REST/gRPC API testing and basic knowledge of UI test automation tools (e.g., Playwright or Selenium).
• CI/CD & Containers: Hands-on experience executing tests within CI/CD pipelines (GitHub Actions/TeamCity) and familiarity with Docker/Kubernetes containerized environments.
• Performance Testing: Demonstrated experience in performance, stress, or scalability testing.
• Interpersonal Skills: Excellent communication and collaboration skills to work effectively across distributed remote teams.

Nice to Have:

• Prior experience with engineering, simulation, or scientific modeling software.
• Knowledge of cloud services (Azure Kubernetes Service, Azure Batch, Azure Blob Storage).
• Experience with database validation (PostgreSQL).
• Exposure to low-level compiled languages (C, C++, or Fortran).

• High impact on quality practices and software development from concept to release.
• A highly collaborative, international, and expert team environment.
• Flexible working model with hybrid office arrangements in Berlin.
• Competitive compensation package and professional growth opportunities.

Our client is a global and independent leader in digital environmental engineering and sustainability solutions. They deliver industry-leading modeling software, advisory services, and cloud platforms dedicated to solving critical water and environmental challenges worldwide.