BI Engineer I, AWS DC Global Network Delivery

Job description

AWS Global Network Delivery Services keeps the cloud running.

We deliver and operate all AWS global infrastructure

every data center, every server, and every cable that gives hundreds of millions of customers uninterrupted access to the services they depend on. We work on some of the hardest supply chain and infrastructure problems in the world, with thousands of variables in play, and we're looking for people who want to help solve them.

You'll join a diverse, cross-functional team of Product managers, TIPMs, network engineers, planners, builders, and operations leaders around the world. Together we work across AWS to deliver the highest standards of safety and security while providing seemingly infinite capacity at the lowest possible cost. Our culture is inclusive, welcomes new ideas, and gives you room to own your work from start to finish.

We're looking for a Business Intelligence Engineer who is curious, learns quickly, and wants to grow by working on real, high-impact problems. You'll build the datasets, metrics, and dashboards that show how infrastructure delivery is performing, from intake through deployment to decommission. You'll work alongside senior BI Engineers, Data Engineers, and business partners to turn business questions into reliable, well-documented data.

What makes this role exciting? Your work won't sit unused. The datasets and dashboards you build will be used every week by planners, operators, and leaders to track delivery milestones and decide what to do next. You'll learn how a global infrastructure business runs, get hands-on with AWS data tools and AI-assisted analytics, and grow your skills through code reviews and mentorship from experienced engineers.

Key job responsibilities

- Work with business stakeholders, TIPMs, and senior team members to gather requirements for well-defined reporting and analysis needs, then translate them into queries, data models, and dashboards.

- Build and maintain datasets, ETL pipelines, and dashboards using SQL, Python, and AWS tools such as Redshift, S3, and QuickSight

- Follow team standards for code reviews, data quality checks, documentation, and monitoring so your work is reliable and reusable

- Run pipeline health checks, investigate data issues, and find the root cause, escalating to the right owners when needed

- Analyze data to answer business questions and clearly explain what you found, including caveats, to stakeholders and your team

- Use metric definitions and the team's data contracts consistently, and point out gaps or inconsistencies you find in source data

- Try out AI tools and new approaches that make analysis faster or more insightful

- Keep learning from code reviews, feedback, and senior teammates, and share what you learn with the team.

A day in the life

A day in the life Your morning starts with dashboard pipeline health checks and a look at new intake requests.

Then you dig into your current project

learning the source data, asking what decision a metric will support, and confirming requirements with your stakeholder before you write code. In the afternoon, you might build or update a dataset, refactor part of a legacy pipeline with guidance from a senior engineer, or walk a stakeholder through a draft dashboard. You finish the day by documenting what you learned and submitting your code for review. You'll be expected to understand a problem before building, and to be open about what you're unsure of.

About the team

We're the PAX Data and Analytics team, a small group of BI Engineers and Data Engineers inside one of the world's largest and fastest-growing data center organizations. We started less than a year ago with one mandate: turn operational complexity into decision-ready clarity.

We do more than build dashboards. We build context that helps leaders act with confidence and helps operators catch problems before they become incidents.

Our work covers the full data lifecycle

sourcing raw operational data, building reliable pipelines, and delivering self-service tools that hundreds of people use every day. Every pipeline we ship and every standard we define becomes the foundation for what comes next. We're young, we're scrappy, and we're building something that will outlast us. It's a great place to learn and grow your career.