Senior Data Analytics Engineer – Fab Planning Analytics at Sandisk

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.