About this role

Amazon is hiring a mid-level Analytics Engineer in the data engineering function based in Tokyo, Japan. The posting calls out experience with Python, R, AWS, SQL. Listed education preference: a bachelor's degree or equivalent.

Role: Analytics Engineer
Function: data engineering
Level: mid
Track: Individual contributor
Employment: Full-time
Location: Tokyo, Japan
Education: Bachelor's degree
Department: Business Intelligence
Posted: May 12, 2026

AI Summary

Mid-level Analytics Engineer analyzing large-scale supply chain data to optimize customer experience and inventory metrics. Partners with Product Managers to identify system defects, benchmark performance, and improve internal products using SQL, Python, and AWS tools on complex datasets.

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Job description

from Amazon careers

About the team
Have you ever ordered a product on Amazon and when that box with the smile arrived, wondered how it got to you so fast? Wondered where it came from and how much it cost Amazon? If so, Amazon’s Supply Chain Optimization Technology (SCOT) organization is for you. At SCOT, we solve deep technical problems and build innovative solutions in a fast-paced environment working with smart & passionate team members. (Learn more about SCOT: http://bit.ly/amazon-scot)
Our vision is to ensure Amazon Customers have the best experience on Amazon, throughout the year, and do not have to compromise with a less than optimal experience during High traffic / Deal events.

SCOT Team is seeking highly motivated individuals with exceptional data analytics skills and a passion for tackling intricate challenges. In this role, you will utilize your expertise to inform impactful business decisions that enhance customer experience and contribute to long-term free cash flow growth. You will gain a comprehensive understanding of Amazon's systems and supply chain processes through collaboration with diverse teams across product, science, tech, retail categories, finance, and operations.

This role will require partnering closely with Product Managers across SCOT to segment our key Customer Experience and Supply Chain metrics, such as SoROOS and Local-In-Stock through the year, identify key opportunities to improve our system and process, to deliver Best-At-Amazon experiences for Customers throughout the year.

Key job responsibilities
• Analyze and synthesize large data streams across multiple systems/inputs.
• Work with Product Managers to understand customer behaviors, spot system defects, and benchmark our ability to serve our customers, improving a wide range of internal products that impact inventory availability for customers both nationally and regionally
• Develop business insights basis data extraction, data analytics, trend deduction & Pattern recognition.
• Present these business insights to senior management/executives.
• Create advanced dashboard to help a large group of teams to consume insights make changes to business process and track progress.
• Build analytical models that can help improve business outcomes at scale enhancing current system abilities.

About the team
Have you ever ordered a product on Amazon and when that box with the smile arrived, wondered how it got to you so fast? Wondered where it came from and how much it cost Amazon? If so, Amazon’s Supply Chain Optimization Technology (SCOT) organization is for you. At SCOT, we solve deep technical problems and build innovative solutions in a fast-paced environment working with smart & passionate team members. (Learn more about SCOT: http://bit.ly/amazon-scot)

Basic Qualifications

- 3+ 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 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

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