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Description

Are you excited to drive analytics strategy for the data center fleet that runs AWS? Do you want to do that work on a platform that pairs traditional BI with the GenAI capabilities that are reshaping the field?

The Central Infrastructure Analytics Team (CIAT) is the unified source for Infrastructure Operations data and business intelligence solutions across AWS's global data center fleet. We support Central Operations leaders running rack install, decommission, repair, logistics, capacity optimization, and network operations.

We are looking for a Senior Business Intelligence Engineer to set the technical bar for analytics across the team, mentor and develop a team of BIEs, and partner directly with senior operations leaders on the metrics and narratives that drive day-to-day decision-making. You will own a customer area or capability domain end-to-end — defining the metric framework, designing the dashboards and Amazon Q topics that customers rely on, and shaping how CIAT delivers analytics enablement at scale.

This role sits at the intersection of three things: deep technical craft (you write the SQL, design the data model, and build the dashboards yourself when it matters), team leadership (you set patterns the rest of the team follows), and strategic partnership (you influence what gets built and what gets sunset). Successful Senior BIEs on this team are equally comfortable in a working session with a director and in a code review with a junior engineer. They treat GenAI as a tool they actively use and shape — not a topic to read about.

Key job responsibilities
- Own a customer area or capability domain end-to-end — KPI definitions, dashboards, Amazon Q topics, WBR/MBR narratives, and the customer relationships that go with them
- Design and lead implementation of analytics frameworks that scale across multiple customer teams — metric taxonomies, measurement standards, and reusable dashboard patterns
- Partner with senior operations leaders to translate strategic questions into metric frameworks and analytics deliverables
- Mentor and develop BIEs through code reviews, design discussions, and project pairing — raising the team's technical bar
- Drive CIAT's analytics enablement strategy — Ambassador Program, dashboard ownership transfers, GenAI-powered self-service for Central Ops customer teams
- Shape how CIAT applies GenAI to analytics — design Amazon Q topics, define LLM-optimized dataset patterns, and establish evaluation practices the team adopts
- Lead complex cross-domain analyses that inform strategic decisions on capacity, repair, logistics, and infrastructure investment
- Evaluate and decide between dashboard implementations proposed by peer BIEs; identify opportunities to consolidate, sunset, or simplify the analytics estate
- Influence data architecture and pipeline priorities by working closely with CIAT's Data Engineering and Systems Development Engineering functions

A day in the life
Most days mix focused build work with leadership time. You might start the morning in a working session with a Senior Manager or Director on the metric framework for a new operational program, then move to a one-on-one with one of CIAT's BIEs walking through a dashboard design they're stuck on. Mid-day, you sit with a Data Engineer on the data model for a new domain, sketch out the Amazon Q topic that will sit on top of it, and code review a peer's pull request. In the afternoon, you draft the WBR narrative for that week's review and join a senior leadership read-out. On a different day, the focus is strategic — auditing the dashboard catalog with the team, deciding what to consolidate or transfer to customer teams, and shaping the next quarter's analytics priorities with the manager.

You will be in front of senior leaders regularly. You will also be hands-on in the data and the tools. The role does not separate those two things.

About the team
CIAT gathers, transforms, and analyzes data for inventory, change-of-state, system health, safety, security, workload, and resource efficiency across AWS's global data center fleet. Our customers are the operations leaders who run rack install, decommission, repair, logistics, capacity optimization, and network operations. We are investing heavily in self-service and GenAI-powered analytics to expand the reach of the team beyond what any one BIE can deliver alone.