Business Intelligence Engineer II, Scot-Fo, PACMAN

Business Intelligence Engineer II, SCOT-FO, PACMAN

Job :  |  Services LLC

The Amazon Supply Chain Optimization Technologies (SCOT) team works on some of the world's most complex supply chain challenges, at Amazon scale. Within SCOT, the Fulfillment Optimization (FO) organization owns products and services that plan and execute orders for the outbound network worldwide — from designing network topology to providing accurate customer promises and selecting optimal fulfillment paths. We are seeking an experienced and motivated Business Intelligence Engineer (BIE) to build analytics and reporting capabilities that power capacity management decisions across Amazon's outbound fulfillment network.

In this role, you will be responsible for designing and developing scalable data solutions that surface capacity utilization trends, identify risk patterns, and generate actionable insights to help optimize how Amazon leverages its fulfillment resources. The ideal candidate is a highly analytical, critical thinker with advanced problem-solving, data mining, and software development skills. You will work closely with software engineers, applied scientists, product managers, and operations stakeholders to translate complex capacity data into business intelligence that informs planning and real-time decision systems.

• 1. Collaborate with software development teams to implement analytics systems to support large-scale data analysis.
• 2. Define, develop, and maintain critical business and operational reports reviewed on a weekly, monthly, quarterly, and annual basis
• 3. Analyze historical data to identify trends and support decision making, including written and verbal presentation of results and recommendations
• 4. Identify data needs and drive data quality improvement projects across multiple data sources and systems
• 5. Understand the broad range of Amazon's data resources, which to use, how, and when
• 6. Provide thought leadership on data mining, analysis, and AI-powered automation to accelerate insight generation
• 7. Build and maintain scalable data pipelines and ETL processes that support real-time and batch analytics use cases
• 8. Partner with cross-functional stakeholders to define metrics, establish baselines, and measure system performance

• 1. Collaborate with the Engineering and Science teams to define new capacity tracking features, construct data pipelines for capacity ingestion and consumption, and validate new system functionalities
• 2. Conduct deep dives into capacity anomalies — such as unexpected capacity breaches, misaligned resource configurations, or consumption spikes — and generate insights for leadership and product management
• 3. Build and maintain dashboards that visualize the end-to-end lifecycle of resource capacity: from initial configuration by resource owners, through real-time consumption tracking, to exhaustion and risk notification
• 4. Analyze differences or discrepancies between expected and actual capacity utilization across outbound resources (sort centers, delivery stations, fulfillment centers)
• 5. Use inputs from capacity resource owners and FO decision system teams to define new data requirements and measurement frameworks
• 6. Support peak event readiness (Prime Day, holiday season) by ensuring capacity data systems are performant, accurate, and providing timely risk signals

The PACMAN (Persistence And Capacity Management) team serves as the centralized authority for capacity availability across all of Amazon's physical outbound resources. Accurate, granular, and real-time capacity tracking is foundational for FO planning and execution systems to effectively utilize first and third party resources. From generating reliable network flow plans to providing accurate customer promises on the website and selecting optimal fulfillment paths for customer shipments, capacity information is a critical input at every step of fulfillment decision making.

• - 3+ years of analyzing and interpreting data with Redshift, Oracle, No
  
  SQL etc. experience
• - 1+ years of SQL, ETL or Oracle experience
• - 1+ years of processing large, multi-dimensional datasets from…