Data Engineer, Global Logistics Product Analytics Team

Join Amazon's Global Logistics Product Analytics team and help shape the future of data-driven decision-making at scale. We are building a centralized data lake across our Global Logistics imports organization and developing the foundation for Gen-AI powered initiatives that empower stakeholders with real-time insights. As a Data Engineer on our team, you will design and deliver production-ready data systems that directly influence how Amazon moves products around the world.

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.

• 1+ years of data engineering experience
• Experience with data modeling, warehousing and building ETL pipelines
• Experience with one or more query language (e.g., SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala)
• Experience with one or more scripting language (e.g., Python, KornShell)