Staff System Design Engineer

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Job Summary
DTPCO is seeking a Senior Product Engineer to translate complex HBM product questions into measurable metrics, trustworthy datasets, and decision-ready analysis that accelerates design-technology-package co-optimization. This role focuses on product data analytics and operational decision support. It requires defining the vital data, making sure it is usable and traceable, and converting it into insights for multi-functional teams to act on. You will collaborate with team members across design, package, process, test, and reliability to align on problem statements, success criteria, and interpretation of results. You will help establish repeatable analytics workflows with validation checks, documentation, and governance so decisions can be made faster and with higher confidence. Success is measured by shorter cycle time from question → data → insight → action, and by adoption of metrics and analysis outputs by partner teams.
Key Responsibilities

• Define and maintain product health and co-optimization metrics spanning electrical, thermal, and mechanical considerations.
• Convert ambiguous multi-functional asks into clear hypotheses, data requirements, and decision criteria.
• Specify data readiness needs (sources, definitions, quality checks, traceability metadata) for repeatable analyses.
• Perform deep-dive analytics to identify drivers of excursions, variability, and performance shifts; summarize findings for technical reviews.
• Partner with design, manufacturing, test, and quality teams to support root cause analysis and corrective action tracking using data-backed evidence.
• Standardize how experiments and analyses are recorded, compared, and reused to enable faster learning loops.
• Develop and maintain dashboards and interactive views of key engineering metrics to improve visibility and triage.
• Keep analytics workflows responsive at scale by profiling bottlenecks and optimizing critical paths.
• Establish pragmatic validation/regression checks for recurring reports and analyses to improve trust and reduce rework.
• Improve discoverability of prior analyses and technical collateral so teams can avoid repeating work.
• Ensure confidential engineering data is handled appropriately with access controls and governance expectations.
• Communicate methods, assumptions, and limitations clearly; document outcomes in an accessible, decision-ready format.

Minimum Qualifications

• Master's degree in Electrical Engineering, Computer Science, Physics (or closely related field).
• Demonstrated experience building/scaling data analytics capabilities used to improve engineering efficiency in sophisticated technical environments.
• Proficiency with SQL and relational database concepts for data discovery and analysis.
• Proficiency with Python for data processing/analysis and workflow automation.
• Experience applying testing/validation practices and systematic debugging/triage to improve reliability of recurring analytics outputs.

Preferred Qualifications

• Familiarity with semiconductor product lifecycle concepts (bring-up, validation, qualification, volume support) and multi-functional interfaces.
• Experience with interactive dashboards or visualization tools used by engineering audiences.
• Experience navigating security/privacy reviews for enterprise analytics or knowledge platforms.
• Exposure to statistical methods for variability analysis, anomaly detection, and root cause support in manufacturing/engineering contexts.
• Domain familiarity with HBM and/or advanced packaging co-optimization workflows (design ↔ fab ↔ assembly ↔ reliability/use-conditions).

Education
Master's degree in Electrical Engineering, Computer Science, Physics (or closely related field).
Working Style / Collaboration

• Turns ambiguous problems into streamlined problem statements, measurable outputs, and clear decision criteria.
• Communicates effectively across disciplines and levels of detail (deep technical ↔ executive summary).
• Biases toward repeatable workflows, documentation, and quality checks that increase trust and adoption.
• Works effectively in governance-aware environments with confidential datasets and access controls.

As a world leader in the semiconductor industry, Micron is dedicated to your personal wellbeing and professional growth. Micron benefits are designed to help you stay well, provide peace of mind and help you prepare for the future. We offer a choice of medical, dental and vision plans in all locations enabling team members to select the plans that best meet their family healthcare needs and budget. Micron also provides benefit programs that help protect your income if you are unable to work due to illness or injury, and paid family leave. Additionally, Micron benefits include a robust paid time-off program and paid holidays. For additional information regarding the Benefit programs available, please see the Benefits Guide posted on micron.com/careers/benefits .
Micron is proud to be an equal opportunity workplace and is an affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, age, national origin, citizenship status, disability, protected veteran status, gender identity or any other factor protected by applicable federal, state, or local laws.
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