AI-Driven BI Engineer II for Real-Time Logistics Analytics

Amazon; Factoria (WA); On-site; USD 100,000 - 160,000; Full time

Benefits offered by this job

Medical, Dental, and Vision Coverage

Paid Time Off (PTO)

401(k) Plan

Job summary

Amazon is seeking a Business Intelligence Engineer II for the Rapid & Rural Logistics (R2L) AI team in Bellevue, WA. You will own end-to-end analytics, design scalable data models, and partner with Data Scientists to integrate predictive models into business workflows.

You’ll build ETL pipelines, define metrics and experiments, and surface descriptive and predictive insights beyond dashboards. Strong SQL and collaboration on AI-driven solutions are essential.

Qualifications

• 3+ years 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

Responsibilities

• Developing performant ETL pipelines
• Defining metrics and experimentation frameworks
• Building intuitive reporting layers that surface both descriptive and predictive insights.

Skills

SQL

Data analysis

Statistics

ETL

Data modeling

Python

Tools

Tableau

Quicksight

AWS

Redshift

Job description

Amazon is seeking a Business Intelligence Engineer II for the Rapid & Rural Logistics (R2L) AI team in Bellevue, WA. You will own end-to-end analytics, design scalable data models, and partner with Data Scientists to integrate predictive models into business workflows.

You’ll build ETL pipelines, define metrics and experiments, and surface descriptive and predictive insights beyond dashboards. Strong SQL and collaboration on AI-driven solutions are essential.