Sr Business Intelligence Engineer III, SCOT - Long Term Planning and Forecasting

About the role

The Supply Chain Optimization Technology (SCOT) team owns Amazon's global inventory planning 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).

Responsibilities

• Design, develop, and maintain scalable analytical solutions, dashboards, and data pipelines using Amazon QuickSight, SQL, and AWS services to track forecast performance across Topline, Inventory, and Capacity planning
• Partner with scientists, engineers, product managers, and cross-functional stakeholders to gather requirements, prioritize initiatives, and deliver data solutions that drive to root cause
• Build and optimize data models, ETL processes, and automated reporting mechanisms that enable data-driven decision making across the organization
• Identify and implement opportunities to integrate generative AI into analytical tools and processes, accelerating insight generation and automating reporting workflows
• Conduct deep-dive analyses to identify trends, patterns, and opportunities for improvement, leading the analytics strategy for complex and ambiguous business questions independently
• Identify and mitigate data quality issues, dependencies, and bottlenecks; escalate and drive resolution as needed
• Take the lead on large projects from start to finish — developing project plans, tracking milestones, and communicating findings effectively to management audiences
• Influence the team's analytics strategy and drive best practices in data modeling, metric definitions, and code quality — continuously improving processes and tools
• Mentor and develop other team members; participate in hiring and technical assessments

Qualifications

• 5+ years of SQL experience
• 5+ years of processing large, multi-dimensional datasets from multiple sources experience
• 5+ years of developing automated reporting experience
• 5+ years of performing statistical analysis experience
• Experience programming to extract, transform and clean large (multi-TB) data sets
• Experience with theory and practice of design of experiments and statistical analysis of results
• Experience with AWS technologies
• Experience in scripting for automation (e.g. Python) and advanced SQL skills
• Experience with theory and practice of information retrieval, data science, machine learning and data mining

Pay

The base salary range for this position is $130,400.00 - $176,300.00 USD annually.