Data Engineer, Worldwide Global Selling AIT

Worldwide Global Selling has been helping individuals and businesses increase sales and reach new customers around the globe. Today more than 50% of Amazons total unit sales come from third-party selection. The Global Selling team in China is responsible for recruiting local businesses to sell on Amazons 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 WWGS-AIT team is positioned to establish AI-ready foundational capabilities across the WWGS 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 WWGS AI and Automation initiatives.


Key job responsibilities
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.
Develop automated data monitoring tools and interactive dashboards to enhance business teams insights into core metrics (e.g. user behavior AI model performance).
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.
Establish data standardization and governance policies to ensure consistency accuracy and compliance.
Provide structured data inputs for AI model training and inference (e.g. LLM applications recommendation systems) optimizing feature engineering workflows.
Explore innovative AI-data integration use cases (e.g. embedding AI-generated insights into BI tools).
Provide technical guidance and best practice on data architecture and BI solution

- 3 years of data engineering experience
- Experience with data modeling warehousing and building ETL pipelines

- 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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