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.
- 5+ years of analyzing and interpreting data with
Redshift,
Oracle, NoSQL etc. experience
- Experience with data visualization using
Tableau, Quicksight, or similar tools
- Experience with
data modeling, warehousing and building
ETL pipelines
- Experience writing complex
SQL queries
- Experience using
SQL to pull data from a database or data warehouse and scripting experience (
Python) to process data for modeling
- Experience developing and presenting recommendations of new metrics allowing better understanding of the performance of the business
- Bachelor's degree in BI, finance, engineering, statistics, computer science, mathematics or equivalent quantitative field
- Experience working directly with business stakeholders to translate between data and business needs
- Experience managing, analyzing and communicating results to senior leadership
- Experience in creating process improvements with automation and analysis, or experience in building financial and operational reports/data sets that inform business decision-making
- Experience in utilizing data and analytical skills to create, measure, and scale workflows to achieve accelerated hiring goals
- Experience in understanding performance metrics and developing them to measure progress against key performance indicators
- Experience reviewing and analyzing performance metrics to identify areas of opportunity that will drive performance improvement
- Experience in building financial and operational reports/data sets that inform business decision-making, or experience in creating process improvements with automation and analysis
- Experience in forecasting analyses
- Experience managing, analyzing and communicating results to senior leadership while working cross functionally across several teams
- Experience with Amazon internal data tools (
Redshift,
Athena, QuickSight) is a plus for internal candidates
- Experience with data center, cloud infrastructure, or hardware operations is valuable but not required — domain knowledge can be learned; analytical rigor cannot
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, OH, Hilliard - 130,400.00 - 176,300.00 USD annually
USA, WA, Seattle - 130,400.00 - 176,300.00 USD annually