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Amazon
Amazon

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Business Intelligence Engineer, Strategic Account Services

职能数据分析
级别中级
地点London, GBR
方式现场办公
类型全职
发布2周前
立即申请

What is the Amazon Marketplace?

Amazon is the largest marketplace on earth. Millions of customers shop in Amazon’s marketplaces globally. Every day, customers browse, purchase, and review products sold by third-party (3P) sellers right alongside products sold by Amazon. Since 2000, Amazon welcomes companies of all sizes to offer their products, helping them reach hundreds of millions of customers, build their brands, and grow their business.

What is Amazon Strategic Account Services (SAS)?

With increasing complexity of today’s e Commerce and rise of opportunities, the SAS Team aims to leverage the full potential of each Amazon selling partner. Our team provides in-depth strategic consultancy using a data-driven, collaborative, and customer-focused approach to achieve commercial goals of our sellers.

What is the role of a BIE?

As a member of the central product team within SAS, you will assist the business teams in making data-driven decisions by transforming raw information into actionable intelligence through the creation of sophisticated data products.

  • Key job responsibilities
  • Gather and translate business requirements into scalable products that work well within the overall data architecture.
  • Develop automated data products including dashboards, reports, self-service tools and data marts.
  • Assist the team in supporting and maintaining the data environment.
  • Assist the team in supporting the business regarding data management and ad-hoc analysis.

Basic Qualifications

  • Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling
  • Experience with data visualization using Tableau, Quicksight, or similar tools
  • Experience with data modeling, warehousing and building ETL pipelines
  • Bachelor's degree in sciences, engineering, finance or equivalent

Preferred Qualifications

  • Experience with AWS solutions such as EC2, DynamoDB, S3, and Redshift
  • Experience in Statistical Analysis packages such as R, SAS and Matlab

Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice (https://www.amazon.jobs/en/privacy_page) to know more about how we collect, use and transfer the personal data of our candidates.

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.

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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

10条评价

3.4

10条评价

工作生活平衡

2.5

薪酬

4.2

企业文化

3.0

职业发展

3.8

管理层

2.7

65%

推荐率

优点

Great benefits and competitive pay

Learning and advancement opportunities

Good teamwork and colleagues

缺点

High pressure and long hours

Poor work-life balance

Toxic work culture and management issues

薪资范围

4个数据点

L2

L6

L3

L4

L5

L2 · Data Analyst L2

0份报告

$108,330

年薪总额

基本工资

$43,332

股票

$54,165

奖金

$10,833

$75,831

$140,829

面试评价

6条评价

难度

4.0

/ 5

时长

21-35周

体验

正面 0%

中性 17%

负面 83%

面试流程

1

Application Review

2

Recruiter Screen

3

Online Assessment

4

Technical Phone Screen

5

Technical Interview

6

Onsite/Virtual Interviews

常见问题

Coding/Algorithm

System Design

Behavioral/STAR

Technical Knowledge