Sr. Business Intelligence Engineer, AWS Analytics Engineering

Amazon is hiring a Sr. Business Intelligence Engineer, AWS Analytics Engineering in Seattle, United States. It pays $130k-$176k a year and Level rates it ; you can apply on Amazon.

Level's read on this job

On Level's scale, this role is Uses AI ●●○○: an ordinary role that requires AI tools.
The posting mentions Slack, Microsoft Office and business intelligence among its tools and skills.
Level classes it as a senior role.
Amazon has 20,000+ other open roles on Level.

AI in this role

Own the analytical roadmap and drive adoption for a generative-AI-powered business intelligence platform.

SlackMicrosoft Office

business-intelligencedata-analysisanalyticsgenerative-ai

AWS is looking for a Sr. Business Intelligence Engineer to join the AWS Analytics Engineering (AAE) team supporting Amazon Quick. Formerly Amazon QuickSight, Quick has evolved from a standalone BI service into a comprehensive, generative-AI-powered business intelligence platform that combines traditional analytics with modern AI assistance. It brings together two complementary experiences. Amazon Quick Sight is the cloud-native dashboarding and visualization engine that powers governed datasets, interactive dashboards, and ML-driven insights such as forecasting and anomaly detection. Alongside it, an agentic AI layer lets users chat with their data, conduct deep research, and automate multi-step workflows across connected enterprise sources through natural language. Available in the browser, as a desktop companion, and through extensions for Slack and Microsoft Office, Quick is used to turn data into decisions and actions, without requiring machine learning expertise. This is your opportunity to shape the analytical foundation of one of AWS's fastest-evolving products.

As a Sr. BIE on this team, you will own the end-to-end analytical roadmap for Amazon Quick. You will generate insights that directly drive adoption, engagement, and growth, and that influence product and feature decisions at the leadership level. You will work with datasets in one of the world's largest data warehousing environments, developing and supporting your hypotheses with data-driven analysis. You will partner closely with product, business, finance, and engineering leaders to tackle non-standard, ambiguous business problems and translate them into actionable output. You will be part of a business intelligence team that goes beyond reporting and drills into the drivers behind key business metrics, redefining best practices with a cloud-based approach to scalability and automation.

Beyond building analytics for Amazon Quick, this team is reimagining how analytical work itself gets done. We are developing agentic capabilities that automate and accelerate the daily workstream of a business intelligence engineer, from building reports to answering analytical questions on demand. As a Sr. BIE, you will help shape and adopt these capabilities, both applying them to scale your own impact and informing how they evolve. This is a rare opportunity to practice business intelligence on a platform you are helping to build, and to redefine analytical best practices for an AI-native era.

Key job responsibilities
- Develop a deep understanding of the business drivers, customer behavior, and data landscape for Amazon Quick.
- Own and deliver a comprehensive reporting and analytical roadmap that surfaces the key metrics for adoption, engagement, and growth.
- Deliver in-depth, data-driven analysis papers with actionable insights for business and product leaders.
- Design and build scalable data pipelines and models to derive key business metrics from large, complex datasets.
- Collaborate with cross-functional teams to identify and onboard new data sources that expand analytical coverage.
- Communicate findings clearly to business, finance, product, and technical audiences to influence decision-making and product enhancements.
- Build and adopt agentic capabilities that automate and accelerate analytical work, from report generation to answering analytical questions on demand.
- Mentor junior engineers and help establish new analytical standards and best practices for the team.

About the team
Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we're building an environment that celebrates knowledge sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future.

Basic qualifications

- 5+ years of SQL experience
- Experience programming to extract, transform and clean large (multi-TB) data sets
- Experience with data modeling, warehousing and building ETL pipelines
- Experience with AWS technologies
- Experience in scripting for automation (e.g. Python) and advanced SQL skills.

Preferred qualifications

- Experience working directly with business stakeholders to translate between data and business needs
- Experience managing, analyzing and communicating results to senior leadership
- Experience with data visualization using QuickSight, Tableau, or similar tools

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 - 130,400.00 - 176,300.00 USD annually

How we rate this

Sr. Business Intelligence Engineer, AWS Analytics Engineering at Amazon rates 45 out of 100 for how much of the daily work is AI. That makes it Uses AI (AI Level 2 of 4). The level is about AI in the job, not seniority.

Classification

Uses AI. An ordinary role that requires AI tools.

●●●● 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.

Key facts

Sr. Business Intelligence Engineer, AWS Analytics Engineering is an open job at Amazon.
Level rates this role AI Level 2 of 4: Uses AI.
The listed salary is $130k-$176k a year.
The role is based in US, WA, Seattle.
The job was posted on September 14, 2026.
Seniority: senior.
Applications are handled by Amazon. Apply on Amazon

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Business IntelligenceData AnalysisAnalyticsGenerative AISlackMicrosoft Office

Questions you could be asked

Tell me about a project where business intelligence was part of your work. What did you do?
Tell me about a project where data analysis was part of your work. What did you do?
Tell me about a project where analytics was part of your work. What did you do?
Tell me about a project where generative ai was part of your work. What did you do?
Walk me through how you've used Slack in your day-to-day work.

Adapt your resume

List these exact terms on your resume: Business Intelligence, Data Analysis, Analytics, Generative AI, and Slack. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Put the AI tool in a bullet point about what you did, not just in a skills list. This role treats it as a required part of the job.

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