Data Engineer , Worldwide Global Selling -AIT

Amazon is hiring a Data Engineer , Worldwide Global Selling -AIT in Beijing, China. Level rates it ; you can apply on Level.

AI in this role

Design AI-ready data pipelines and engineer agentic systems to power seller intelligence and automation in global selling.

ai-agentsdata-engineeringetldata-pipelinesdata-governance

Worldwide Global Selling has been helping individuals and businesses increase sales and reach new customers around the globe. Today, more than 50% of Amazon's total unit sales come from third-party selection. The Global Selling team in China is responsible for recruiting local businesses to sell on Amazon’s 19+ overseas marketplaces and supporting local Sellers’ success and growth on the Amazon. Our vision is to be the first choice for all types of Chinese business to go globally.
The Worldwide Global Selling Analytics, Intelligence, and Technology (WWGS-AIT) team serves as the research, automation, and insight arm of the International Seller Service data hub, enabling rapid delivery of growth insights through strategic investments in regional data foundations, self-service business intelligence solutions, and artificial intelligence tools.
The AGS-AIT team is positioned to establish AI-ready foundational capabilities across the AGS organization while maintaining excellence in business insight generation, and self-service BI/AI application development.

AIT is building the next generation of AI-ready data capabilities across the WWGS organization. We are looking for a Senior AI Agent & Data Engineer who can bridge modern data engineering with AI agent development — designing the data foundation that powers our AI applications while directly engineering agentic systems that drive seller intelligence and automation.

Key job responsibilities
• Design and implement end-to-end data pipelines (batch and streaming) for data collection, transformation, and storage — supporting both AI application and analytics use cases
• Build and maintain integration layer data models that serve as a unified, AI-ready data foundation across WWGS domains
• Develop automated data quality monitoring, alerting, and observability tooling to ensure pipeline reliability and data trustworthiness
• Integrate multi-source data (seller behavior, transaction logs, off-platform signals, AI outputs) into a coherent, governed data layer
• Establish data standardization and governance policies ensuring consistency, accuracy, and compliance across AI and BI consumption layers
• Design and implement end-to-end data pipelines (ETL) to ensure efficient data collection, cleansing, transformation, and storage, supporting both real-time and offline analytics needs.
• Collaborate with cross-functional teams (e.g., Product, Operations, Tech) to align data logic, integrate multi-source data (e.g., user behavior, transaction logs, AI outputs), and build a unified data layer.
• Provide structured data inputs for AI model training and inference (e.g., LLM applications, recommendation systems), optimizing feature engineering workflows.

About the team
The Worldwide Global Selling Analytics, Intelligence, and Technology (WWGS-AIT) team serves as the research, automation, and insight arm of the International Seller Service data hub, enabling rapid delivery of growth insights through strategic investments in regional data foundations, self-service business intelligence solutions, and artificial intelligence tools.
The AGS-AIT team is positioned to establish AI-ready foundational capabilities across the AGS organization while maintaining excellence in business insight generation, and self-service BI/AI application development.

WWGS-AIT is looking for a Data Engineer to collaborate with cross-functional teams to design and develop data infrastructure and analytics capabilities for AGS AI and Automation initiatives.

Basic qualifications

- 3+ years of data engineering experience
- 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)

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 , Worldwide Global Selling -AIT at Amazon rates 70 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 , Worldwide Global Selling -AIT 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 14, 2026.
Seniority: senior.
Applications are handled by Amazon. Apply on Amazon

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

AI agentsData EngineeringETLData PipelinesData Governance

Also common in data engineer jobs at this level

SQL Python Spark Machine learning Azure Airflow

Pay

Typical data engineer job: $145k

This posting doesn't list pay. Use the typical data engineer figure when pay comes up. See data engineer jobs

Questions you could be asked

How do you decide when an AI agent can act on its own versus asking for approval first?
Tell me about a project where data engineering was part of your work. What did you do?
Tell me about a project where etl 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 data governance was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: AI agents, Data Engineering, ETL, Data Pipelines, and Data Governance. 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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