Business Intelligence Engineer II, AWS DC Central Operations
Amazon is hiring a Business Intelligence Engineer II, AWS DC Central Operations in Seattle, United States. It pays $100k-$160k a year and Level rates it ; you can apply on Amazon.
Level's read on this job
- On Level's scale, this role is Little AI ●○○○: aI is not part of the work.
- Level classifies it as a mid-level role.
- Level lists 21,000+ other open roles at Amazon.
- The role was posted in the last few days.
AI in this role
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 Business Intelligence Engineer to design and own customer-facing analytics products and to drive analytics adoption across our customer teams. You will partner with operations leaders to translate business questions into measurable KPIs, build dashboards and metric layers in QuickSight, and increasingly leverage GenAI tools — Amazon Q, natural language query interfaces, and retrieval-augmented analytics — to multiply your impact across thousands of users.
Successful BIEs on this team are customer-obsessed, comfortable with operational ambiguity, and equally interested in building great dashboards and in teaching customers to build their own. They write strong SQL, communicate clearly with non-technical leaders, and treat GenAI as a tool they actively use rather than a topic to read about.
Key job responsibilities
- Design, build, and maintain dashboards and analytical reporting solutions in QuickSight that support InfraOps decision-making
- Partner with business and technical stakeholders to translate operational questions into KPIs, data products, and Weekly and Monthly Business Review (WBR/MBR) narratives
- Develop and present recommendations to senior leaders, including written narratives and verbal walk-throughs of insights
- Design Amazon Q topics and supporting datasets that enable customer analysts to self-serve on questions previously requiring a CIAT engagement
- Use CIAT's GenAI tools — Amazon Q, natural language query interfaces, and retrieval-augmented analytics — as a primary part of the job
- Contribute to CIAT's analytics enablement programs that train Central Ops analysts on BI tools, query platforms, and GenAI capabilities
- Write SQL against the team's data warehouse and datalake to validate metrics, investigate data quality issues, and prototype analytics
A day in the life
Most days mix a few hours of focused build work — SQL development, dashboard iteration, metric validation — with stakeholder time. You might join a working session with a Logistics or Capacity Optimization team to walk through a metric definition, then sit with one of their analysts to review a query they wrote against CIAT's datalake. After lunch you might pair with a Data Engineer on the data model behind a new WBR metric, draft the narrative for that week's review, and review another BIE's pull request before logging off. On a different day, the focus is an Amazon Q topic for a domain that has been generating repeat ad-hoc requests — designing the supporting dataset, configuring synonyms, and testing answers against real questions customers have asked.
You will be in front of customers regularly — not constantly, but enough that you should enjoy that side of the work. The team partners closely with Data Engineers and Systems Development Engineers, so you will rarely be the only person on a problem.
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.
Basic qualifications
- 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
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, WA, Seattle - 99,500.00 - 160,000.00 USD annually
How we rate this
Business Intelligence Engineer II, AWS DC Central Operations at Amazon rates 7 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.
Little AI. AI is not part of the work.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
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