Application deadline: Mar 17, 2026

Amazon Web Services (AWS) builds and operates the infrastructure behind the world's largest cloud platform. Within AWS, the Global Capacity & Infrastructure Development (GCID) organization is responsible for the design, planning, procurement, delivery, and operation of all global infrastructure — including data centers, networking, power, and cooling systems that keep the cloud running for millions of customers worldwide.

We're looking for a Business Intelligence Engineer to join a high-impact team that turns complex infrastructure and supply chain data into clear, actionable insights for leadership. No prior experience in data center or telecom infrastructure is required — what matters is your ability to learn a new domain quickly, ask the right questions, and build reliable, scalable BI solutions.

You'll use your analytical and engineering skills to contribute to insightful discussions with leadership and help the team anticipate the future direction of large-scale programs. You'll ensure the BI solutions you own are accurate, timely, accessible, and actionable. You're comfortable owning significant work streams end to end and delivering high-quality results with minimal guidance.

You contribute to team strategy and take ownership of key components of the team's infrastructure. You make things simpler. You follow and advocate for BI engineering best practices: code reviews, syntax and naming conventions, metric definitions, and alarms. You dig into the root cause(s) of problems rather than treating symptoms, and your work may help unblock adjacent efforts. You collaborate effectively across team boundaries when needed.

Key job responsibilities
Collaborate with cross-functional teams to design, develop, and maintain end-to-end complex performance metrics and visualizations to monitor and report business performance

Collect, analyze, and interpret large datasets from diverse sources to identify trends and patterns

Implement data governance best practices to ensure data accuracy, consistency, and compliance with security and privacy regulations

Proactively identify opportunities to improve data quality, performance, and usability of existing dashboards and reports

Design, build, and maintain end-to-end ETL pipelines from the ground up — from raw data ingestion through transformation and delivery to downstream consumers

Work on data pipelines, data models, and leverage the AWS infrastructure tech stack to build tracking metrics and related visualizations

Provide technical guidance and support to stakeholders in leveraging dashboards and data insights to enhance decision-making processes

A day in the life
You will partner with teams across supply chain, deployment operations, finance, legal, and business development to track the cost, timeline, and performance of large-scale network infrastructure projects. You'll build end-to-end ETL pipelines and analytics solutions using AWS services — ingesting data from multiple sources, transforming it into reliable datasets, and surfacing insights through dashboards that drive real decisions. You will be a valued analytical partner with the opportunity to take ownership of meaningful projects and grow your impact across the organization.

About the team
Our team builds the data platform and analytics that power decision-making for AWS's global capacity & infrastructure fiber organization. We collect data from dozens of sources, build automated ETL pipelines, and deliver dashboards that help leaders track large-scale construction and deployment programs against cost, schedule, and performance targets.

We're a small, collaborative team where everyone has real ownership. You'll work directly with program managers, finance, and operations stakeholders. Our stack is AWS-native — S3, Glue, Athena, Redshift, and Quick Sight. The domain is complex but learnable; what matters most is curiosity and strong engineering fundamentals.

Basic Qualifications

• 3+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
• 3+ years of SQL, ETL or Oracle experience
• 2+ years of developing automated reporting experience
• 2+ years of processing large, multi-dimensional datasets from multiple sources experience
• Experience with forecasting and statistical analysis
• Experience with data visualization using Tableau, Quicksight, or similar tools
• 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
• Building statistical models and automated ML pipelines

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

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.

USA, CO, Denver - 99,500.00 - 160,000.00 USD annually