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Engineer Product Engineering (f/m/d)DresdenHRC1854073
Infineon · Posted 15 days ago
"Own yield performance during volume production and drive root-cause analysis across test, design, and manufacturing data at a global power and IoT semiconductor leader."
Do you have deep technical expertise, a strong affinity for data and enjoy getting to the bottom of complex analytical challenges? In this role, you will combine your technical expertise with data-driven analysis to identify correlations across test and manufacturing data and derive targeted measures to optimize the quality and yield of our products. Your role Key responsibilities in your new role Analyze and correlate data from parametric tests, functional tests and manufacturing processes using advanced analytical methods and tools Identify and perform in-depth analyses of yield detractors related to design, test and technology, and derive appropriate improvement measures Optimize product yield and quality and evaluate manufacturing experiments in close collaboration with experts from different technical areas Analyze new products and take ownership of yield performance during volume production, including wafer disposition following functional testing Develop and apply digitalization methods to efficiently analyze and evaluate complex technical data Contribute to international product development projects and regularly report on yield performance and analysis results to internal and external stakeholders Your profile You enjoy digging deep into technical challenges and complex data, identifying patterns and correlations, and systematically investigating issues to understand their root causes. You combine strong analytical skills and technical curiosity with a high affinity for data, computers and digital tools. At the same time, you communicate your findings effectively and enjoy collaborating with experts across different functions. …
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There are 28 open roles at Infineon right now. This role is one of 9,090 Software Engineer openings and centers on Product Engineering, Yield Analysis, Failure Analysis, and Data Analysis.
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