AmazonData Engineer, Global Logistics Product Analytics Team
Amazon is hiring a Data Engineer, Global Logistics Product Analytics Team in Bellevue, United States. It pays $132k-$179k a year and Level rates it ; you can apply on Amazon.
Level's read on this job
- On Level's scale, this data engineer role is Works on AI ●●●○: the daily work is on AI products, without building the model.
- Tools and skills the posting cites include Bedrock, AWS and Redshift.
- Level classifies it as a mid-level role.
- Level lists 21,000+ other open roles at Amazon.
AI in this role
Data Engineer building scalable ETL pipelines and experimenting with generative AI tools like AWS Bedrock for logistics analytics.
Key job responsibilities
- Design, build, and maintain scalable ETL pipelines and CI/CD infrastructure to support business and operational performance reporting
- Manage and administer data platforms built on AWS services including Redshift, Kinesis, S3, and Lambda
- Develop and improve data architecture, data quality monitoring, and data availability across the organization
- Build and experiment with Gen-AI tools such as AWS Bedrock to support intelligent data solutions
- Partner with Business Intelligence Engineers, Product Managers, and other data roles to enable data-driven program decisions
- Develop scalable frameworks for data instrumentation in collaboration with partner tech teams
- Continuously improve self-service reporting and analysis processes for internal customers
A day in the life
Your day will be dynamic and impactful, involving collaborative work with cross-functional teams to develop sophisticated data architectures. You'll design and implement robust ETL pipelines, experiment with generative AI tools, and continuously refine our data ecosystem to support critical business decisions.
About the team
The Global Logistics Product Analytics team is dedicated to transforming logistics operations through innovative, centralized data solutions. We value technical creativity, collaborative problem-solving, and the ability to turn complex data into clear insights. Our team is building the data foundation that powers intelligent, data-driven strategies across Amazon's global supply chain.
Basic qualifications
- 3+ years of data engineering experience
- 1+ years of developing and operating large-scale data structures for business intelligence analytics using ETL/ELT processes experience
- 1+ 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
- 1+ years of developing and operating large-scale data structures for business intelligence analytics using Oracle experience
- 3+ years of in the job offered or a related occupation experience
- 1+ years of developing and operating large-scale data structures for business intelligence analytics using each of the following: ETL (Extract, Transform, Load)/ELT (Extract, Load, Transform) processes experience
- Bachelor's degree or foreign equivalent in Computer Science, Engineering, Information Systems, Mathematics, or a related field
- Experience with data modeling, warehousing and building ETL pipelines
Preferred qualifications
- Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, 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)
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 - 132,100.00 - 178,800.00 USD annually
How we rate this
Data Engineer, Global Logistics Product Analytics Team at Amazon rates 65 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in data engineer jobs at this level
Pay
- This job starts at
- $132k
- Typical data engineer job
- $150k
This posting starts 12% below the typical data engineer job. See data engineer jobs
Questions you could be asked
- Tell me about a project where etl was part of your work. What did you do?
- Tell me about a project where data engineering was part of your work. What did you do?
- Tell me about a project where data modeling was part of your work. What did you do?
- Tell me about a project where ci/cd was part of your work. What did you do?
- Tell me about a project where generative ai was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: ETL, Data Engineering, Data Modeling, CI/CD, and Generative AI. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.
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