Business Intelligence Engineer II, 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

• 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
• Collaborate with scientists, engineers, and product managers to gather requirements and deliver data solutions that surface root-cause insights
• Build and maintain data models, ETL processes, and automated reporting mechanisms that enable data-driven decision making
• Leverage generative AI tools and techniques to accelerate insight generation and automate reporting workflows
• Conduct deep-dive analyses to identify trends, patterns, and opportunities for improvement
• Proactively identify data quality issues, dependencies, and bottlenecks
• Own and deliver medium-complexity projects from start to finish
• Adopt and champion team best practices in data modeling, metric definitions, and code quality
• Support onboarding of new team members and contribute to knowledge-sharing initiatives

Qualifications

• 3+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
• 1+ years of SQL, ETL or Oracle experience
• 1+ years of processing large, multi-dimensional datasets from multiple sources experience
• 1+ years of performing statistical analysis experience
• 1+ years of developing automated reporting experience
• Experience with data visualization using Tableau, Quicksight, or similar tools
• Experience with data modeling, warehousing and building ETL pipelines
• Experience in Statistical Analysis packages such as R, SAS and Matlab
• Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling