AmazonPosted 1mo ago
Data Engineer , Worldwide Global Selling -AIT at Amazon scores 68 out of 100 on AI centrality, which makes it AI Level 3 of 4 (Works on AI) on this board. The level measures how much of the work is AI, not seniority.
AI in this role
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)
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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
Questions you could be asked
- How do you decide when an AI agent can act on its own versus asking for approval first?
- Describe a typical day in a role like this one: which parts run through AI directly?
- If you removed AI from this role, what would be left, and how do you decide what still needs a human?
Adapt your resume
- List these exact terms on your resume: AI Agents. 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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