Staff Engineer, Product
Operations & Manufacturing
- Regular Fulltime
Place of employment
What we offer:
Your tasks and responsibilities
- Responsible to define yield target for new product and develop roadmap for continuos yield improvement.
- Interface with multiple stakeholders from Design, New Product Development, Test, Packaging, Reliability, Operations and Quality Engineering teams to support new product development, product qualification and ramp up activities, ensuring product meeting commited timeline and achive best in class yield and quality.
- Compile and analyze data using common statistical anlysis methodology and effectively present key results & conclusion along with recommended actions.
- Analyze products to ensure manufacturability and data sheet compliance, this includes supporting design challenge, OEMD, DFM review etc, continuously feedback to development team.
- Lead cross functional team to solve yield issue, manage excursions and questionable material disposition.
- Assume product ownership after product release and acts as a central interface for all product issues
- Engage in group problem-solving and process improvement projects.
- Employ appropriate Statistical Process Control (SPC) principles to reduce variability in product performance.
- Interface with development team to drive effective FMEA’s and risk reduction assessment
Your education and experiences
- Bachelor's degree in Electrical Engineering or comparable technical discipline (Master's preferred)
- At least 5 years of Product Engineering or equivalent experience in a semiconductor environment
- Oral and written English language proficiency is a must
- Expertise in statistical analysis and statistical software (JMP, Spotfire, Excel, etc.)
- Strong stakeholder management skill, ability to interface effectively and to build consensus with coworkers at every level of the company
- Time management skills for balancing multiple high-priority activities
- Must have strong attention to detail, be self-motivated and able to achieve results with minimal supervision