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# Business Intelligence Engineer, Data Center Capacity Delivery Tooling

- **Company:** Amazon.com, Inc.
- **Location:** Seattle, WA, United States
- **Salary:** $99,500.0 - $160,000.0
- **Contract:** Permanent contract
- **Skills:** Amazon Web Services, Amazon Elastic Compute Cloud, Amazon S3, Data Analysis, Databases, Data Centers, Information Engineering, Data Infrastructure, Extract Transform Load (ETL), Data Mining, Data Systems, Data Visualization, Data Warehousing, Amazon DynamoDB, R (Programming Language), Python (Programming Language), MATLAB, NoSQL, Oracle (Applications), SAS (Software), SQL Databases, Tableau (Software), Data Processing, Scripting, System Availability, Information Technology, Data Analytics, AWS Data Analytics, Amazon Redshift
- **Published:** October 27, 2026
- **Apply:** https://dejobs.org/x/x/0BD9F29F651D491E93BC2058EFED01BE/job/

## About the Role

* 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
 * 3+ years of in the job offered or a related occupation experience
 * 1+ years of using SQL, ETL (Extract, Transform, Load), or Oracle experience
 * Bachelor's degree or foreign equivalent in Computer Science, Engineering, Mathematics, Statistics, Economics, or a related field
 * 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

Preferred Qualifications

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

## Description

As a Business Intelligence Engineer (BIE), you will drive data excellence, provide data reporting, visualizations, automations, and insights for the Data Center Capacity Delivery Team. Candidates will be customer obsessed in their pursuit of data clarity and reporting. Successful candidates have track records of partnering with cross functional teams to create data alignment and visibility of data to enable businesses to make optimal resourcing decisions.

We are looking for someone with a broad background of data automation, strong business acumen, who takes ownership of their work, and is focused on customer needs. The successful candidate will communicate crisply to management. They will have an ability to make data-driven conclusions and will be comfortable with ambiguity while working in a fast-paced dynamic environment.

AWS Infrastructure Services owns the design, planning, delivery, and operation of all AWS global infrastructure. In other words, we're the people who keep the cloud running. We support all AWS data centers and all of the servers, storage, networking, power, and cooling equipment that ensure our customers have continual access to the innovation they rely on.

You'll join a diverse team of project managers, construction managers, controls engineers, commissioning engineers, and other vital roles. You'll collaborate with people across AWS to help us deliver the highest standards for safety and security while providing seemingly infinite capacity at the lowest possible cost for our customers. And you'll experience an inclusive culture that welcomes bold ideas and empowers you to own them to completion., * Design, implement and support an analytical data infrastructure

 * Continually improve ongoing reporting and analysis processes, automating or simplifying self-service support for customers
 * Work closely with business partners and recruiting to support ongoing efforts
 * Build automated data solutions in QuickSight
 * Deep dive data to understand and resolve discrepancies
 * Communicate actions/recommendations to customers/stakeholders in both written and verbal formats
 * Create reports highlighting key insights and trends

*Create source-of-truth datasets using SQL; you leverage scripting language i.e. Python to create automation and reduce manual processes

 * Partner with Data Engineering to enhance data infrastructure, data availability, and broad access to customer insights