Business Intelligence Engineer II, SCOT - Long Term Planning and Forecasting

Where will Amazon's growth come from next year? In five years? Which product lines are staged to quintuple in size, and which ones are mature? Are we investing enough in our infrastructure, or too much? How will our customers react to changes in prices, or selection, or delivery speed? The SCOT Long-Term Planning and Forecasting (LTPF) team works to answer these key questions. The Supply Chain Optimization Technology (SCOT) team owns Amazon's global inventory planning systems: SCOT decides what, when, where, and how much inventory to buy in order to meet customer needs as well as Amazon's business goals. We do this for millions of items, for hundreds of product lines worth billions of dollars of inventory world-wide. Our systems are built entirely in-house, and represent the forefront of automated large scale supply chain planning and optimization systems.. SCOT LTPF is responsible for long-term forecasting and planning across Topline, Inventory, and Capacity — helping Amazon plan key metrics including ordered units and GMS, inventory units and cost, and FC building capacity and topology (size and location). SCOT LTPF is looking for a Business Intelligence Engineer to support the team. LTPF BI Engineers build and maintain analytical tools supporting Topline, Inventory, and Capacity planning, and engage with internal stakeholders and external consumers of LTPF forecasts to ensure they have timely data in the right context to answer key business questions. The ideal candidate will have experience in leading analytics projects including but not limited to: forecasting, business monitoring, business intelligence and data visualization. The candidate should also have experience mapping analytical solutions to business problems in the most ambiguous environments with a track record of making data easy to consume for end users. This position will require extensive stakeholder and project management. Key job responsibilities - Develop and maintain analytical dashboards, reports, and data pipelines using Amazon QuickSight, SQL, and AWS services to track forecast performance across Topline, Inventory, and Capacity planning — following established architectural patterns and team standards to ensure solutions are reliable and well-documented - Collaborate with scientists, engineers, and product managers to gather requirements and deliver data solutions that surface root-cause insights — escalating trade-offs and prioritization decisions to senior team members when needed - Build and maintain data models, ETL processes, and automated reporting mechanisms that enable data-driven decision making — optimizing for performance and reliability within the team's existing frameworks - Leverage generative AI tools and techniques to accelerate insight generation and automate reporting workflows, contributing ideas for new AI-driven improvements to the team's analytical processes - Conduct deep-dive analyses to identify trends, patterns, and opportunities for improvement — delivering clear findings on well-scoped business questions and contributing to analyses on more complex or ambiguous problems with guidance from senior team members - Proactively identify data quality issues, dependencies, and bottlenecks — troubleshooting and resolving issues within scope and escalating broader systemic problems with clear documentation - Own and deliver medium-complexity projects from start to finish — developing project plans, tracking milestones, and communicating findings clearly to team leads and stakeholders - Adopt and champion team best practices in data modeling, metric definitions, and code quality — proactively identifying opportunities to improve processes and tools within your area of ownership - Support onboarding of new team members and contribute to knowledge-sharing initiatives; participate in hiring loops and technical assessments as a bar raiser candidate (with development support) A day in the life LTPF BI Engineers focus on