Senior Engineer, Data Analytics Engineering

Sandisk understands how people and businesses consume data and we relentlessly innovate to deliver solutions that enable today’s needs and tomorrow’s next big ideas. With a rich history of groundbreaking innovations in Flash and advanced memory technologies, our solutions have become the beating heart of the digital world we’re living in and that we have the power to shape.

Sandisk meets people and businesses at the intersection of their aspirations and the moment, enabling them to keep moving and pushing possibility forward. We do this through the balance of our powerhouse manufacturing capabilities and our industry-leading portfolio of products that are recognized globally for innovation, performance and quality.

Sandisk has two facilities recognized by the World Economic Forum as part of the Global Lighthouse Network for advanced 4IR innovations. These facilities were also recognized as Sustainability Lighthouses for breakthroughs in efficient operations. With our global reach, we ensure the global supply chain has access to the Flash memory it needs to keep our world moving forward.

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

Requirements

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

Nice to have

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