Business Intelligence Engineer - SCOT, Fulfillment Optimization, SCOT-FO; Fulfillment & Operations

Business Intelligence Engineer - SCOT, Fulfillment Optimization, SCOT-FO

Every Amazon customer order passes through the Fulfillment Optimization (FO) Team, which determines the most cost‑effective fulfillment strategy while meeting delivery promises. This role will work within the Supply Chain Optimization Technology (SCOT) Group, where you will build data pipelines and automated reporting systems to support forecasting and decision‑making across Amazon’s fulfillment network.

Key responsibilities include:

• Own the data architecture and reporting infrastructure for UPB, DDF, and CPP forecasting inputs across U.S. and international marketplaces.
• Build and maintain automated pipelines that produce weekly forecast bridges, variance decompositions, and accuracy tracking consumed by leadership (W , Q , OP cycles).
• Develop AI‑assisted analytical workflows that automate recurring analyses, anomaly detection, and root‑cause investigation across large‑scale forecasting datasets.
• Partner with research scientists and economists to validate model outputs, back‑test forecast accuracy, and translate model improvements into measurable business impact.
• Design and build self‑service dashboards and data products that enable product managers and scientists to explore forecast performance independently.
• Mine and integrate data from simulation results, log files, fulfillment systems, and transportation datasets to identify trends, quantify risks, and support planning decisions.
• Drive data quality improvement projects—defining data contracts, monitoring freshness/completeness, and building alerting systems that surface issues before downstream consumers are affected.
• Collaborate with software development teams to implement analytics systems and data structures that support machine‑learning model delivery and large‑scale experimentation.

A typical day starts with an overnight variance report that you review and share with leadership, followed by building back‑testing infrastructure for new models, root‑cause analysis of data drift, and developing an AI agent that automates a weekly report. You also spend time reviewing teammates’ code changes and iterating on forecasting pipelines.

Benefits for full‑time employees typically include:

• Medical, Dental, and Vision coverage
• Maternity and parental leave options
• Paid Time Off (PTO)
• 401(k) plan

• 3+ years of analyzing and interpreting data with Redshift, Oracle, No
  
  SQL, etc.
• 1+ years of SQL, ETL, or Oracle experience
• 1+ years of processing large, multi‑dimensional datasets from multiple sources
• 1+ years of performing statistical analysis
• 1+ years of developing automated reporting
• Experience with data visualization using Tableau, Quick Sight, or similar tools
• Experience with data modeling, warehousing, and building ETL pipelines
• Experience with 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
• Experience with Data & AI technologies, including AI/ML, GenAI, analytics, database, and/or storage

• Experience with AWS solutions such as EC2, DynamoDB, S3, and Redshift
• Experience in data mining, ETL, and using databases in a business environment with large‑scale, complex datasets

Amazon is an equal‑opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

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