Senior Engineer, Data Analytics Engineering

ESSENTIAL DUTIES AND RESPONSIBILITIES: 

• Perform data mining and analytics for Quality Assurance (QA) in semiconductor Assembly & Testing processes
• Understand QA business workflows (e.g., SPC, 8D, defect management) and translate business needs into scalable data solutions
• Design and develop end-to-end data pipelines, including data ingestion, transformation, modeling, and visualization
• Develop analytical methods such as anomaly detection, trend analysis, and predictive modeling to enhance quality control
• Drive the transformation of quality management from manual processes to automated and intelligent systems
• Develop dashboards, reports, and automated QA-related business applications
• Collaborate with IT, data teams, and business stakeholders to integrate data platforms with operational systems
• Explore and implement AI/GenAI use cases in quality engineering, such as intelligent insights and automated reporting

REQUIRED:

• Bachelor’s degree or above in Computer Science, Data Science, Industrial Engineering, Electrical Engineering, or related fields
• 2-5 years of experience in data analytics or data engineering; experience in manufacturing or QA/QC is preferred
• Proficiency in Python and SQL for data processing and analysis
• Strong programming skills in Python, Java, Scala, or similar languages
• Experience in data modeling and ETL/ELT pipeline design
• Familiarity with at least one BI tool (e.g., Power BI, Tableau)
• Basic understanding of quality methodologies (e.g., SPC, 8D, FMEA)
• Strong analytical thinking and problem-solving skills
• Good communication skills with the ability to work across cross-functional and global teams
• Fluent in English for professional communication

PREFERRED:

• Experience in the semiconductor industry, especially in Assembly & Testing
• Hands-on experience in developing QA systems (e.g., 8D systems, defect tracking platforms)
• Experience in machine learning or AI projects (e.g., anomaly detection, predictive analytics)
• Exposure to GenAI applications (e.g., LLMs, Copilot, automated report generation)
• Familiarity with cloud platforms such as AWS, Azure, or Google Cloud
• Experience with big data technologies (e.g., Spark, Kafka)
• Software development experience (e.g., web applications, APIs, microservices architecture)
• Understanding of digital transformation frameworks or data-driven quality systems
• Mandarin Chinese proficiency is a plus for effective collaboration with China-based teams

Sandisk thrives on the power and potential of diversity. As a global company, we believe the most effective way to embrace the diversity of our customers and communities is to mirror it from within. We believe the fusion of various perspectives results in the best outcomes for our employees, our company, our customers, and the world around us. We are committed to an inclusive environment where every individual can thrive through a sense of belonging, respect and contribution.

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