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职位Amazon

Data Engineer, ORBIT (AMZL operational reporting and BI)

Amazon

Data Engineer, ORBIT (AMZL operational reporting and BI)

Amazon

Austin, TX, USA

·

On-site

·

Full-time

·

3d ago

Have you ever ordered a product on Amazon and when that box with the smile arrived you wondered how it got to you so fast? Have you wondered where it came from and how much it cost Amazon to deliver it to you? If so, the WW Amazon Logistics, Business Analytics team is for you. We manage the delivery of tens of millions of products every week to Amazon’s customers, achieving on-time delivery in a cost-effective manner.

Amazon is looking for a passionate, results-oriented Data Engineer to help build the next generation of analytics for Amazon Logistics. In this role, you will work at the intersection of data engineering and AI to transform how Last Mile decisions are made. You will design and build scalable data systems and contribute to agentic solutions that enable leaders to access insights, metrics, and root cause analysis in a seamless and intuitive way.

As a Data Engineer on the Orbit (AMZL operational reporting and BI) team, you will operate in one of the most complex data and agentic solution environments at Amazon. You will focus on organizing and structuring large-scale datasets that power critical business metrics across Last Mile delivery, while enabling AI-driven use cases such as automated insights, RCA generation, and conversational analytics. You will work with modern AWS technologies and evolving AI capabilities (e.g., Bedrock, event-driven architectures, real-time data systems) to build reliable, low-latency, and cost-efficient data solutions. This is a high-impact role where you will partner closely with product, engineers, and business stakeholders to translate complex requirements into scalable data products.

You will thrive here if you:

1. Are excited about building data solutions that power AI and agentic workflows
2. Continuously learn and apply new technologies to solve real business problems
3. Can design simple, scalable solutions in complex and ambiguous environments
4. Care deeply about data quality, ownership, and building reliable systems at scale

Key job responsibilities
1. Build and deploy agentic AI solutions to improve Last Mile analytics and decision-making

2. Continuously evaluate and adopt evolving AI/ML technologies (e.g., Bedrock, Bedrock Agents / Agent Core, other AWS Services) and apply them to real business problems

3. Own and drive data quality initiatives for Lastmile, focusing on scalable and reliable solutions

4. Help the team scale by building simple, maintainable systems and mentoring junior engineers

Basic Qualifications

  • 3+ years of data engineering experience
  • 2+ years of developing and operating large-scale data structures for business intelligence analytics using ETL/ELT processes experience
  • 2+ years of developing and operating large-scale data structures for business intelligence analytics using OLAP technologies experience
  • 1+ years of developing and operating large-scale data structures for business intelligence analytics using data modeling experience
  • 1+ years of developing and operating large-scale data structures for business intelligence analytics using SQL experience
  • Knowledge of professional software engineering & best practices for full software development life cycle, including coding standards, software architectures, code reviews, source control management, continuous deployments, testing, and operational excellence
  • Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS

Preferred Qualifications

  • Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, Fire Hose, Lambda, and IAM roles and permissions
  • Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)
  • Experience building large-scale, high-throughput, 24x7 data systems

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, TX, Austin - 132,100.00 - 178,800.00 USD annually
USA, WA, Bellevue - 132,100.00 - 178,800.00 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

3.4

10条评价

工作生活平衡

2.3

薪酬

4.2

企业文化

3.1

职业发展

3.8

管理层

2.7

65%

推荐给朋友

优点

Great benefits and competitive compensation

Learning opportunities and career advancement

Good teamwork and colleagues

缺点

High pressure and long hours

Poor work-life balance

Toxic work culture and high turnover

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

6次面试

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