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amazon

Posted via Amazon Jobs

Business Intelligence Engineer II, SCOT-FO, PACMAN

Posted Aug 29, 2026

Role at a glance

Job function
AI & Data Data Analytics
Salary
$99.5K – $160K/yr
Location
Bellevue, Washington, United States
Work arrangement
On-site
Employment
Full-time
Education
Bachelor's

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Qualifications

Required

  • 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
  • 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

Preferred

  • Experience in data mining, ETL, etc. and using databases in a business environment with large-scale, complex datasets
  • Experience with statistical analysis, co-relation analysis

About the role

Original posting provided by amazon

View original
The Amazon Supply Chain Optimization Technologies (SCOT) team works on some of the world's most complex supply chain challenges, at Amazon scale. Within SCOT, the Fulfillment Optimization (FO) organization owns products and services that plan and execute orders for the outbound network worldwide — from designing network topology to providing accurate customer promises and selecting optimal fulfillment paths.

We are seeking an experienced and motivated Business Intelligence Engineer (BIE) to build analytics and reporting capabilities that power capacity management decisions across Amazon's outbound fulfillment network. In this role, you will be responsible for designing and developing scalable data solutions that surface capacity utilization trends, identify risk patterns, and generate actionable insights to help optimize how Amazon leverages its fulfillment resources.

The ideal candidate is a highly analytical, critical thinker with advanced problem-solving, data mining, and software development skills. You will work closely with software engineers, applied scientists, product managers, and operations stakeholders to translate complex capacity data into business intelligence that informs planning and real-time decision systems.

Key job responsibilities
1. Collaborate with software development teams to implement analytics systems to support large-scale data analysis.
2. Define, develop, and maintain critical business and operational reports reviewed on a weekly, monthly, quarterly, and annual basis
3. Analyze historical data to identify trends and support decision making, including written and verbal presentation of results and recommendations
4. Identify data needs and drive data quality improvement projects across multiple data sources and systems
5. Understand the broad range of Amazon's data resources, which to use, how, and when
6. Provide thought leadership on data mining, analysis, and AI-powered automation to accelerate insight generation
7. Build and maintain scalable data pipelines and ETL processes that support real-time and batch analytics use cases
8. Partner with cross-functional stakeholders to define metrics, establish baselines, and measure system performance

A day in the life
1. Collaborate with the Engineering and Science teams to define new capacity tracking features, construct data pipelines for capacity ingestion and consumption, and validate new system functionalities
2. Conduct deep dives into capacity anomalies — such as unexpected capacity breaches, misaligned resource configurations, or consumption spikes — and generate insights for leadership and product management
3. Build and maintain dashboards that visualize the end-to-end lifecycle of resource capacity: from initial configuration by resource owners, through real-time consumption tracking, to exhaustion and risk notification
4. Analyze differences or discrepancies between expected and actual capacity utilization across outbound resources (sort centers, delivery stations, fulfillment centers)
5. Use inputs from capacity resource owners and FO decision system teams to define new data requirements and measurement frameworks
6. Support peak event readiness (Prime Day, holiday season) by ensuring capacity data systems are performant, accurate, and providing timely risk signals

About the team
The PACMAN (Persistence And Capacity Management) team serves as the centralized authority for capacity availability across all of Amazon's physical outbound resources. Accurate, granular, and real-time capacity tracking is foundational for FO planning and execution systems to effectively utilize first and third party resources. From generating reliable network flow plans to providing accurate customer promises on the website and selecting optimal fulfillment paths for customer shipments, capacity information is a critical input at every step of fulfillment decision making.

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
- 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 in data mining, ETL, etc. and using databases in a business environment with large-scale, complex datasets
- Experience with statistical analysis, co-relation analysis

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
amazon

About the company

amazon

Large Enterprise

Amazon is a global leader in e-commerce and cloud computing, founded in 1994 by Jeff Bezos. Initially starting as an online bookstore, it has since expanded its offerings to include a vast range of products and services, including electronics, fashion, and digital content. With Amazon Web Services (AWS), the company also provides powerful cloud solutions to businesses around the world. Known for its innovation, customer-centric approach, and commitment to operational efficiency, Amazon continues to shape the future of retail and technology, consistently seeking new ways to enhance customer experiences.