Data Engineer - AI/ML Products, AOP (Analytics Operations and Programs)

Amazon is hiring a Data Engineer - AI/ML Products, AOP (Analytics Operations and Programs) in Beijing, China. Level rates it ; you can apply on Level.

AI in this role

Data Engineer building and maintaining scalable data pipelines and infrastructure to support AI/ML model development and production deployment.

data-engineeringpythonci-cddata-pipelinesmachine-learning-infrastructure

The AOP (Analytics Operations and Programs) team is responsible for creating core analytics, insight generation and science capabilities for ROW Ops. We develop scalable analytics applications, AI/ML products and research models to optimize operation processes. You will work with Product Managers, Data Engineers, Data Scientists, Research Scientists, Applied Scientists and Business Intelligence Engineers using rigorous quantitative approaches to ensure high quality data/science products for our customers around the world. As a Data Engineer, you will play a crucial role in supporting the team by creating and maintaining the data infrastructure necessary for the advanced analytics and machine learning solutions.

Our team solves a broad range of problems that can be scaled across ROW (Rest of the World including countries like India, Australia, Singapore, MENA and LATAM). Here is a glimpse of the problems that this team deals with on a regular basis:

• Using live package and truck signals to adjust truck capacities in real-time
• HOTW models for Last Mile Channel Allocation
• Using LLMs to automate analytical processes and insight generation
• Ops research to optimize middle mile truck routes
• Working with global partner science teams to affect Reinforcement Learning based pricing models and estimating Shipments Per Route for $MM savings
• Deep Learning models to synthesize attributes of addresses
• Abuse detection models to reduce network losses

Key job responsibilities
1. Design, develop, and maintain scalable data pipelines to support AI/ML model development and production deployment.
2. Implement and maintain CI/CD pipelines for the data and AI/ML solutions.
3. Collaborate with data scientists and other team members to understand data requirements and implement efficient data processing solutions.
4. Create and manage data warehouses and data lakes, ensuring proper data governance and security measures are in place.
5. Collaborate with product managers and business stakeholders to understand data needs and translate them into technical requirements.
6. Stay current with emerging technologies and best practices in data engineering, and propose innovative solutions to improve data infrastructure and processes for AI/ML models and analytics applications.
7. Participate in code reviews and contribute to the development of best practices for data engineering within the team.

About the team
The AOP (Analytics Operations and Programs) team is responsible for creating core analytics, insight generation and science capabilities for ROW Ops. We develop scalable analytics applications, AI/ML products and research models to optimize operation processes. You will work with Product Managers, Data Scientists, Research Scientists, Applied Scientists and Business Intelligence Engineers using rigorous quantitative approaches to ensure high quality data/science products for our customers around the world.

Basic qualifications

- Experience with data modeling, warehousing and building ETL pipelines
- 3+ years of data engineering experience
- Knowledge of at least two of the following programming languages: Scala, Java, Python, C/C++, or Go
- Knowledge of cloud services such as AWS or equivalent
- Experience with version control systems and CI/CD pipeline implementation

Preferred qualifications

- Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)
- Experience with training and deploying AI/ML systems to solve large-scale optimizations
- Experience working with data analytics
- Experience with big data technologies

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.

How we rate this

Data Engineer - AI/ML Products, AOP (Analytics Operations and Programs) 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.

Classification

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. Open the description and count.

Key facts

Data Engineer - AI/ML Products, AOP (Analytics Operations and Programs) is an open job at Amazon.
Level rates this role AI Level 3 of 4: Works on AI.
The role is based in CN, 13, Beijing.
The job was posted on October 8, 2026.
Seniority: mid.
Applications are handled by Amazon. Apply on Amazon

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

Data EngineeringPythonCi CdData PipelinesMachine Learning Infrastructure

Questions you could be asked

Tell me about a project where data engineering was part of your work. What did you do?
Tell me about a project where python 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 data pipelines was part of your work. What did you do?
Tell me about a project where machine learning infrastructure was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: Data Engineering, Python, Ci Cd, Data Pipelines, and Machine Learning Infrastructure. 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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