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Sr. Data Engineer, Amazon Freight

Amazon

Sr. Data Engineer, Amazon Freight

Amazon

Bellevue, WA, USA

·

On-site

·

Full-time

·

2w ago

Amazon Freight is a startup business within Amazon focused on developing an industry-leading transportation offering to provide external freight Customers access to the world-class network and freight services currently used to facilitate Amazon’s own freight movements. Our freight offerings/portfolio ensures our Customer’s freight is moved with the highest level of service and quality at a competitive price across multiple modes of transportation, including truckload, less-than-truckload, and intermodal. In doing this, Amazon is deeply studying customer shipping needs and building innovative, market-leading solutions that will organically attract customers towards our services.

  • As a Sr. Data Engineer in Amazon Freight Data Analytics team, you will
  • Build robust and scalable data integration (ETL) pipelines using SQL, EMR, Python and Spark.
  • Build and deliver high quality data architecture to support business intelligence engineer and program managers’ reporting needs.
  • Interface with other technology teams to extract, transform, and load data from a wide variety of data sources.
  • Drive both business and technology solutions to improve Amazon Inbound visibility.
  • Continually improve ongoing reporting and analysis processes, automating or simplifying self-service support for customers.
  • Translate data into actionable insights for the stakeholders.

Basic Qualifications

  • 5+ years of data engineering experience
  • Experience with data modeling, warehousing and building ETL pipelines
  • Experience with SQL
  • Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS
  • Experience mentoring team members on best practices

Preferred Qualifications

  • Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
  • Experience operating large data warehouses

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 - 154,600.00 - 209,100.00 USD annually

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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

L2

L3

L4

L5

L6

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