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Data Engineer Internship - 2027 (US)

Detected 1 hour ago · no stated deadline, so apply early: rolling reviews close without warning

Who can apply

Applicants must have a minimum of one quarter, semester, or trimester remaining in their studies after the internship concludes.

About the role

Data Engineer Internship - 2027 (US) - Job ID: 10553907 | Amazon.jobs Skip to main content × Home Teams Locations Job categories My career My applications My profile Account security Settings Sign out Resources Accommodations Benefits Inclusive experiences How We Hire Leadership principles Working at Amazon FAQ Data Engineer Internship - 2027 (US) Job ID: 10553907 | Amazon.com Services LLC Apply now Description Shape what comes next | Discover careers in Tech At Amazon, our tech isn't just a tool, it's your playground. Our engineers work on scalable systems, cloud services, and customer-facing products that operate at global scale. This is an environment where you learn by building. Whether you're creating cloud-native solutions, optimizing machine learning models, or building products that drive experiences for millions of customers around the globe, your work reaches the world, fast. You'll take ownership early, collaborate across teams and disciplines, and grow your skills as you tackle new problems. There's no single path forward here, with a chance to explore different directions and shape your journey as you go. This is where ambition meets opportunity and, where the impact of what you build helps define what comes next, for customers and for you. What's in it for you? An internship at Amazon means real responsibility from day one. You'll build, test, and learn alongside people who want to see you succeed, while making an impact that reaches far beyond campus. 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. 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 2027) 2. Summer (Starts May/June 2027) 3. Fall (Starts August/September 2027) 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 as 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

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