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.
From there, you might spend time building a new data pipeline to support a product launch, optimizing a slow-running query, or working with an analyst to figure out the best way to model a tricky dataset. No two days look exactly the same, but the common thread is solving data problems that directly impact how customers shop for groceries.
You'll partner closely with analysts, scientists, and business teams across areas like product selection, pricing, promotions, and customer growth. Sometimes you'll go beyond your regular responsibilities — jumping into an urgent data investigation, prototyping a new automation, or helping a teammate debug a complex issue.
The pace is fast, the problems are real, and the work you do shows up in how millions of customers experience grocery shopping on Amazon.
About the team
We're a team of analysts, data engineers, and software developer who are passionate about one thing: making grocery shopping better for customers around the world. Our mission is to build the data foundation that helps Amazon's grocery business — including Amazon Fresh and Whole Foods Market — make faster, smarter decisions across different products and how customers find what they need.
We work in a collaborative, curiosity-driven environment where everyone's ideas matter. You'll sit alongside people who love solving puzzles with data, and you'll partner with product teams, business leaders, and engineers across the grocery organization. We believe great data infrastructure is invisible to the end user but transformative for the business — and we take pride in building systems that are reliable, scalable, and easy to understand.
Our culture values ownership, learning, and transparency. We celebrate wins together, share knowledge openly, and support each other through challenges. Whether you're building your first production pipeline or mentoring a teammate through a tricky problem, you'll find a team that invests in your growth and trusts you to make an impact from day one.
- 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)
- Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
- Experience with any ETL tool like, Informatica, ODI, SSIS, BODI, Datastage, etc.
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.