Advanced Packaging Central Planning: Strategic/Scenario Planning Principal Engineer

We are seeking a Principal Engineer to lead strategic and scenario planning for Advanced Packaging Central Planning. This role owns end-to-end scenario development across the Business Planning (BP) horizon and long-range planning horizon, translating product roadmaps, market signals, and technology/ramp constraints into optimized capacity and loading strategies. You will drive capital efficiency by evaluating tradeoffs across cost, capex timing, ramp agility, inventory strategy, and market share/bit growth, and by delivering clear, decision-ready recommendations to senior leadership.
 

Key Responsibilities

• Lead and govern scenario studies across business plan and long-range horizons, including scenario baselines, assumptions management, and change control to ensure traceability and alignment to business goals.

• Develop and run scenario optimization to define optimum loading plans that balance output and market share with qualification milestones, ramp readiness, and capacity thresholds.

• Quantify capital impacts: develop and maintain Cost of Transition (CoT); assess gaps between budget vs. actuals; explain cause–effect relationships driving tooling and capital deltas.

• Own long-range space and footprint demand planning, translating product/technology roadmaps into expansion pathways (site and tooling mix, infrastructure readiness, and ramp phasing) under uncertainty.

• Recommend manufacturing strategies to inform senior leadership investment decisions by framing scenario-driven tradeoffs and providing clear guidance on capital allocation and prioritization (capex timing/scale and tooling plans) aligned to long-range business and technology objectives.

• Partner with Central teams, Manufacturing, Technology Development, Finance, and Product teams to align product roadmaps to capacity and capital plans

• Communicate scenario insights to executive and cross-functional stakeholders through structured narratives, visualizations, and decision/logic trees, highlighting risks, opportunities, and sensitivity to key assumptions.

• Own scenario data pipelines and databases; define governance for data quality, versioning, and auditability across planning studies.

• Identify and lead automation opportunities to streamline planning workflows, improve forecast accuracy, and eliminate manual errors; prototype or partner with analytics/IT to deploy sustainable solutions.

• Lead complex, cross-site projects and mentor/guide other engineers on scenario methodology and optimization approaches

Requirements

• Bachelor’s or Master’s degree in Industrial Engineering, Operations Research, Supply Chain, Data Analytics, Engineering, or related discipline (advanced degree preferred).

• 8–10+ years of experience in semiconductor manufacturing planning, capacity/capital planning, industrial engineering, supply chain planning, or advanced packaging/assembly planning, with demonstrated ownership of cross-functional planning deliverables.

• Proven expertise in scenario planning across multiple horizons (annual BP and multi-year long-range), including assumptions governance, sensitivity analysis, and decision framing.

• Strong optimization and quantitative modeling skills (e.g., linear/integer programming, simulation, heuristic optimization, or comparable methods) applied to loading, capacity allocation, and capex efficiency.

• Ability to translate complex technical and business inputs (technology qualification gates, ramp curves, tool constraints, yield/throughput levers) into practical plans and executive-ready recommendations.

• Advanced data and analytics capability (e.g., SQL, Python/R, Power BI/Tableau, Excel modeling); able to build repeatable models and automate workflows.

• Excellent stakeholder management and communication skills, including influencing without authority and presenting to senior leadership.

• Demonstrated project leadership across departments/sites; experience driving standard work, change control, and continuous improvement.

• Preferred: deep knowledge of scenario, capacity and capital planning methodologies (e.g., constraint/bottleneck modeling, what-if scenario analysis, and long-range capex planning); advanced packaging manufacturing flow familiarity is a plus.