Data Engineer , WWGS GRIT

Are you excited about building data infrastructure that powers one of the world's largest grocery businesses? We're looking for a Data Engineer to design, develop, and maintain scalable data pipelines that drive critical business decisions across Amazon's grocery portfolio — including Amazon Fresh, Whole Foods Market, and more.

In this role, you'll build and optimize data workflows, develop data models, and create robust infrastructure that supports analytics across areas like product selection, pricing, promotions, marketing, and how customers discover groceries online. You'll collaborate with analysts, scientists, engineers, and product teams to deliver high-quality, reliable data solutions that enable smarter decisions at a global scale.

This is an opportunity to work on complex, high-impact data challenges in a fast-paced environment where your contributions directly influence how millions of customers shop for groceries.

Key job responsibilities Design, develop, and maintain scalable ETL/ELT pipelines to ingest, transform, and load data from multiple sources into Amazon's data warehouse and data lake environments.

Build and optimize data models that support reporting, analytics, and machine learning use cases across WWGS domains.

Write efficient and well-structured SQL queries and scripts to process large-scale datasets. Monitor, troubleshoot, and resolve data pipeline failures to ensure data availability and reliability within defined SLAs.

Collaborate with Business Intelligence Engineers, Data Scientists, and business stakeholders to understand data requirements and deliver fit-for-purpose data solutions.

Implement data quality checks, validations, and alerting mechanisms to ensure accuracy and completeness of data.

Develop and maintain technical documentation for data pipelines, data models, and system architecture.

Participate in code reviews and contribute to engineering best practices within the team.

Support the automation of manual data processes to improve operational efficiency.

Work with big data technologies (Spark, Hive, EMR) and AWS services to build performant data infrastructure at scale

A day in the life Your primary focus is making sure clean, reliable data flows to the people who need it — every single day. You'll start your morning checking pipeline health, fixing any issues that popped up overnight, and ensuring teams have the data they need to make decisions.