Smart Signal Testing Specialist

Capgemini Engineering is a global leader in engineering services, providing R&D and engineering solutions across all industries. The company supports innovative projects such as autonomous cars and life-saving robots and operates with a global team of engineers, scientists, and architects. Capgemini is a responsible and diverse global organization with over 410,000 team members in more than 50 countries, achieving €22.5 billion in revenue in 2025. It combines AI, technology, and human ingenuity to help enterprises transform and grow using expertise in AI, cloud, and data.

• Solid experience (5+ years) in software testing or quality assurance with strong QA methodologies, test plan design, and iterative execution processes.
• Proven hands-on proficiency in Python (v3.6+), capable of writing, maintaining, and optimising scripts for testing and automation.
• Experience working with time-series data and validating complex, data-intensive workflows.
• Strong analytical and debugging skills, able to investigate technical issues, identify root causes, and communicate findings clearly.
• Knowledge of Smart Signal platforms (Cloud and/or On-Premises) and Asset Performance Management (APM) environments is a strong advantage.

• Design and execute comprehensive test plans and validation strategies for end-to-end Blueprint processes in Smart Signal, ensuring logic paths between anomaly alerts and business workflows function accurately and reliably.
• Work hands-on with time-series data to validate data-heavy processes, ensuring data integrity and consistency across Smart Signal platforms, both Cloud and On-Premises.
• Develop and maintain robust Python (v3.6+) scripts to support testing, automation, and validation activities across the Smart Signal environment.
• Proactively debug complex issues and conduct deep-dive root-cause analyses on failing test scenarios, translating technical findings into clear, actionable insights and performance improvements.
• Apply strong QA methodologies and iterative test execution practices to continuously improve testing coverage, quality, and efficiency across Blueprint validation cycles.