Data Engineer Internship - Fall 2026 (US)

Amazon•Seattle, WA

1d•$101,300 - $160,000•Onsite

About The Position

Amazon is seeking Data Engineer Interns for Fall 2026. These are full-time, in-office positions, requiring interns to work Monday-Friday, up to 40 hours per week, typically between 8am-5pm. Interns should not have conflicts with classes or other employment during work hours and must have at least one quarter/semester/trimester remaining in their studies after the internship. This role offers the opportunity to design tools and infrastructure for analyzing large data volumes, solve big data warehousing problems, and partner with stakeholders to implement data solutions. Interns will join one of Amazon's many lines of business, working alongside experienced engineers, and will be matched with a manager and a mentor. The program provides hands-on learning, opportunities for personal and professional development, networking, and participation in intern activities. Applicants will be considered for roles across various US locations, including the Greater Seattle Area, Greater Bay Area, Greater DMV, Austin, New York City, and Minneapolis, with specific location and start date finalized at the time of job offer.

Requirements

Are 18 years of age or older
Work 40 hours/week minimum and commit to 12 week internship maximum
Are enrolled in an academic program that is physically located in the United States
Experience with data transformation
Experience with database, data warehouse or data lake solutions
Experience with SQL
Experience with one or more scripting language (e.g., Python, KornShell, Scala)
Currently enrolled in or will receive a Bachelor’s Degree, Master's Degree, or advanced technical degree in Computer Science, Computer Engineering, Information Management, Information Systems, or an equivalent technical discipline with an expected conferral date between October 2026 – December 2029.

Nice To Haves

Experience with AWS
Experience building data pipelines or automated ETL processes
Knowledge of writing and optimizing SQL queries in a business environment with large-scale, complex datasets
Experience with big data processing technology (e.g., Hadoop or ApacheSpark), data warehouse technical architecture, infrastructure components, ETL, and reporting/analytic tools and environments
Experience with data visualization software (e.g., AWS QuickSight or Tableau) or open-source project
Experience from previous technical internship(s) or demonstrated project experience
Knowledge of basics of designing and implementing a data schema like normalization, relational model vs dimensional model

Responsibilities

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.