Senior Data Analytics Engineer – Fab Planning Analytics

Company Description

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.

Job Description

Sandisk is seeking a senior-level Data Analytics Engineer to drive high-impact analytics in support of our Central Fabrication Planning function. In this role, you will turn complex manufacturing and planning data into influential, actionable recommendations that improve factory outcomes with our manufacturing partner. You will operate as a technical leader—owning analytics problem framing, data exploration, modeling, and stakeholder communication—while innovating new methods to increase planning effectiveness, execution predictability, and operational performance. You will closely collaborate with the Global Operations team, including the Japan team.

Essential Duties and Responsibilities: 

• Partner with Central Fab Planning to define high-value questions, success metrics, and decision workflows; translate ambiguous problems into analytic deliverables and recommendations.
• Deliver actionable insights that influence manufacturing outcomes, such as capacity utilization, WIP/cycle time, bottleneck management, demand-supply alignment, yield impacts to plan, and execution variance.
• Build and maintain analytics solutions using daily hands-on work with:
  • data querying (SQL and related query tools),
  • scripting/programming (Python and/or equivalent),
  • datasets across multiple sources (manufacturing systems, planning systems, operational databases, logs).
• Develop robust data pipelines and data quality practices to ensure analytic outputs are trusted, reproducible, and scalable (e.g., ETL/ELT, validation checks, monitoring).
• Create decision-ready outputs (dashboards, reports, structured analyses, scenario comparisons) that highlight tradeoffs, risks, and next best actions.
• Apply advanced analytics / statistical methods (and where appropriate, ML/optimization) to improve planning accuracy and operational decisions.
• Communicate fluently in English (Japanese as optional), including delivering executive-level summaries, facilitating working sessions, and translating technical/operational nuance across global teams.
• Mentor and influence across functions—helping teams adopt data-driven practices and raising analytic maturity through standards, reusable code, and best practices.
• Occasional international travel to collaborate with global stakeholders and manufacturing partner teams.

Qualifications

Required:

• Advanced degree (M.S. or Ph.D.) in Engineering, Computer Science, Data Science, Statistics, Operations Research, Industrial Engineering, Physics, or a related discipline.
• 8+ years of professional experience in data analytics in an engineering/manufacturing/industrial setting.
• Extensive semiconductor industry experience (target: ~10 years), with demonstrated exposure to production operations and decision cycles.
• Daily professional proficiency with:
  • SQL / database querying (complex joins, performance-minded query patterns),
  • programming/scripting (Python preferred; R/Scala/Java acceptable depending on ecosystem),
  • analytics workflows (data wrangling, exploratory analysis, automation, reproducibility).
• Strong ability to convert analysis into clear recommendations that decision makers can act on—under constraints, imperfect data, and competing priorities.

Preferred: 

• Deep experience in semiconductor factory operations, especially fab planning, production execution, and mass production environments (e.g., capacity planning, WIP management, cycle time, tool productivity, constraint/bottleneck analysis).
• Experience with scenario modeling, simulation, or optimization methods (e.g., linear programm