Data Engineer Internship - 2026 (US)

Amazon Data Engineer Internship

Amazon internships across all seasons are full-time positions, and interns should expect to work in office, Monday-Friday, up to 40 hours per week typically between 8am-5pm. Specific team norms around working hours will be communicated by your manager. Interns should not have conflicts such as classes or other employment during the Amazon work-day. Applicants should have a minimum of one quarter/semester/trimester remaining in their studies after their internship concludes. By applying to this position, your application will be considered for all Data Engineer roles at all locations we hire for in the United States including but not limited to: Greater Seattle Area (Seattle, Bellevue, Redmond), Greater Bay Area (San Francisco, Sunnyvale, Santa Clara), Greater DMV (DC, MD, VA), Austin (TX), New York City (NY), Minneapolis (MN). You will be able to provide your preference of location and start date during the application process but, we cannot guarantee that we can meet your selection based on several factors including but not limited to the availability and business needs of this role. Finalization on the location and start dates available will be provided to you at the time of job offer.

Start dates for our internships in this posting include the following periods:

1. Winter (Starts January/February 2026)
2. Summer (Starts May/June 2026)
3. Fall (Starts August/September 2026)

Do you love building data pipelines? Are you excited by the opportunity to design tools and infrastructure needed to analyze large volumes of data? Do you want to help solve big data warehousing problems, and partner with stakeholders to understand how to best design and implement cutting edge data solutions that provide answers to key business questions? Do you want to be a part of a fast-paced environment and contribute to one of the most visited sites on the Internet? If this describes you, consider joining us as an Amazon is looking for a data engineer intern to join one our many lines of business. Amazon interns have the opportunity to work alongside the industry's brightest engineers who innovate every day on behalf of our customers. You will be matched to a manager and a mentor. You will have the opportunity to impact the evolution of Amazon technology as well as lead mission critical projects early in your career. Your work will contribute to solving some of the most complex technical challenges in the company.

Key Job Responsibilities

As a Data Engineer intern, you will/may:

• Design, implement, and automate deployment of our distributed system for collecting and processing log events from multiple sources.
• Design data schema and operate internal data warehouses and SQL/NoSQL database systems.
• Own the design, development, and maintenance of ongoing metrics, reports, analyses, and dashboards that engineers, analysts, and data scientists use to drive key business decisions.
• Monitor and troubleshoot operational or data issues in the data pipelines.
• Drive architectural plans and implementation for future data storage, reporting, and analytic solutions.
• Develop code based automated data pipelines able to process millions of data points.
• Improve database and data warehouse performance by tuning inefficient queries.
• Work collaboratively with Business Analysts, Data Scientists, and other internal partners to identify opportunities/problems.
• Provide assistance with troubleshooting, researching the root cause, and thoroughly resolving defects in the event of a problem.

A day in the life

Our internship program provides hands-on learning and building experiences for students who are interested in a career in data engineering. In addition to working on an impactful project, you will have the opportunity to engage with Amazonians for both personal and professional development, expand your network, and participate in fun activities with other interns throughout the summer. No matter the location of your internship, we give you the tools to own your internship and learn in a real-world setting.