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职位Amazon

Sr. BIE, Amazon Global Selling -AIT

Amazon

Sr. BIE, Amazon Global Selling -AIT

Amazon

Shanghai, 31, CHN

·

On-site

·

Full-time

·

1w ago

Amazon Global Selling has been helping individuals and businesses increase sales and reach new customers around the globe. Today, more than 50% of Amazon's total unit sales come from third-party selection. The Global Selling team in China is responsible for recruiting local businesses to sell on Amazon’s 19+ overseas marketplaces and supporting local Sellers’ success and growth on the Amazon. Our vision is to be the first choice for all types of Chinese business to go globally.

  • Key job responsibilities
  • Design, develop, and maintain scalable data infrastructure and ETL pipelines to support business intelligence initiatives using automated dashboard solutions
  • Partner with Product, Technical, Business, and Marketing teams to understand data requirements and design scalable and user-friendly BI solutions
  • Design and implement AI/LLM-powered solutions to automate human-in-the-loop tasks
  • Design and develop statistical analysis to support business decision making using the AI infrastructure and company wide solutions

About the team
The Amazon Global Selling Analytics, Intelligence, and Technology (AGS-AIT) team serves as the research, automation, and insight arm of the International Seller Service data hub, enabling rapid delivery of growth insights through strategic investments in regional data foundations, self-service business intelligence solutions, and artificial intelligence tools.
The AGS-AIT team is positioned to establish AI-ready foundational capabilities across the AGS organization while maintaining excellence in business insight generation, and self-service BI/AI application development.

AGS-AIT is looking for a Senior Business Intelligence Engineer to collaborate with cross-functional teams to design and develop data infrastructure and analytics capabilities for AGS AI and Automation initiatives.

Basic Qualifications

  • 10+ years of professional or military experience
  • 8+ years of SQL experience
  • Experience programming to extract, transform and clean large (multi-TB) data sets
  • Experience with theory and practice of design of experiments and statistical analysis of results
  • Experience with AWS technologies
  • Experience in scripting for automation (e.g. Python) and advanced SQL skills.
  • Experience with theory and practice of information retrieval, data science, machine learning and data mining

Preferred Qualifications

  • Experience working directly with business stakeholders to translate between data and business needs
  • Experience managing, analyzing and communicating results to senior leadership

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.

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关于Amazon

Amazon

Amazon

Public

Amazon.com, Inc. is an American multinational technology company engaged in e-commerce, cloud computing, online advertising, digital streaming, and artificial intelligence.

10,001+

员工数

Seattle

总部位置

$1.5T

企业估值

评价

2.9

10条评价

工作生活平衡

2.8

薪酬

3.7

企业文化

2.5

职业发展

2.3

管理层

2.1

35%

推荐给朋友

优点

Good pay and compensation

Strong benefits package

Flexible scheduling options

缺点

Poor management and leadership

Limited growth and promotion opportunities

High stress and demanding work environment

薪资范围

4个数据点

Junior/L3

L2

L3

L4

L5

L6

M3

M4

M5

M6

Mid/L4

Principal/L7

Senior/L5

Staff/L6

Director

Junior/L3 · Data Scientist L4

0份报告

$181,968

年薪总额

基本工资

-

股票

-

奖金

-

$154,672

$209,264

面试经验

10次面试

难度

3.7

/ 5

时长

21-35周

录用率

20%

体验

正面 10%

中性 10%

负面 80%

面试流程

1

Application Review

2

Recruiter Screen

3

Online Assessment

4

Technical Phone Screen

5

Onsite/Virtual Loop

6

Team Matching

7

Offer

常见问题

Coding/Algorithm

System Design

Behavioral/STAR

Leadership Principles

Technical Knowledge