AmazonBusiness Intelligence Engineer - SCOT, Fulfillment Optimization, SCOT-FO LRN
Amazon is hiring a Business Intelligence Engineer - SCOT, Fulfillment Optimization, SCOT-FO LRN in Bellevue, United States. It pays $100k-$160k a year and Level rates it ; you can apply on Amazon.
Level's read on this job
- Level rates this role Works on AI ●●●○: the daily work is on AI products, without building the model.
- The posting mentions Python, SQL and AWS among its tools and skills.
- Level classes it as a mid-level role.
- Amazon has 21,000+ other open roles on Level.
AI in this role
Build data pipelines, automated reporting, and AI-assisted analytical workflows for supply chain fulfillment forecasting.
We are part of Amazon's Supply Chain Optimization Technology (SCOT) Group, which develops systems that optimize inventory placement, transportation, and fulfillment plans across marketplaces worldwide.
The FO Planning & Forecasting team is seeking a Business Intelligence Engineer (BIE) who combines deep analytical skills with a builder's mindset — someone who can architect data pipelines, develop automated reporting systems, and apply AI-powered tooling to accelerate insight generation and decision-making at scale.
Key job responsibilities
- Own the data architecture and reporting infrastructure for LA, IRA and DLA forecasting inputs across US and international marketplaces
- Build and maintain automated pipelines that produce weekly forecast bridges, variance decompositions, and accuracy tracking consumed by leadership (WBR, QBR, OP cycles)
- Develop AI-assisted analytical workflows that automate recurring analyses, anomaly detection, and root-cause investigation across large-scale forecasting datasets
- Partner with research scientists and economists to validate model outputs, backtest forecast accuracy, and translate model improvements into business impact ($M attribution)
- Design and build self-service dashboards and data products that enable product managers and scientists to independently explore forecast performance without ad-hoc requests
- Mine and integrate data across simulation results, log files, fulfillment systems, and transportation datasets to identify trends, quantify risks, and support planning decisions
- Drive data quality improvement projects — defining data contracts, monitoring freshness/completeness, and building alerting systems that surface issues before they reach downstream consumers
- Collaborate with software development teams to implement analytics systems and data structures that support ML model delivery and large-scale experimentation
A day in the life
Your morning starts with an automated variance report your pipeline generated overnight — IRA missed plan, and the system already attributed the gap to a drop in inventory availability. You add context and push the summary to leadership before 10am. Mid-day, you're building backtesting infrastructure for a scientist's new model, then pairing with a partner team to root-cause an unexpected data drift. In the afternoon, you're developing an AI agent that automates a recurring weekly report — retrieving data, computing breakdowns, and drafting the narrative with human review before publishing. You end the day reviewing a teammate's code change that adds a new marketplace to a forecasting pipeline. The thread across it all: building systems that make the team faster and the forecasts more reliable.
Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment.
The benefits that generally apply to regular, full-time employees include:
- Medical, Dental, and Vision Coverage
- Maternity and Parental Leave Options
- Paid Time Off (PTO)
- 401(k) Plan
If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you!
At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply!
Basic qualifications
- 3+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
- 3+ years of SQL, ETL or Oracle experience
- 3+ years of processing large, multi-dimensional datasets from multiple sources experience
- 3+ years of performing statistical analysis experience
- 3+ years of developing automated reporting experience
- 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, Bellevue - 99,500.00 - 160,000.00 USD annually
How we rate this
Business Intelligence Engineer - SCOT, Fulfillment Optimization, SCOT-FO LRN at Amazon rates 65 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● 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.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Questions you could be asked
- How do you decide when an AI agent can act on its own versus asking for approval first?
- Tell me about a project where data architecture was part of your work. What did you do?
- Tell me about a project where forecasting was part of your work. What did you do?
- Tell me about a project where data pipelines was part of your work. What did you do?
- Tell me about a project where business intelligence was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: AI agents, Data Architecture, Forecasting, Data Pipelines, and Business Intelligence. 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.
- Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.
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