Data Engineer Internship

We are looking for curious individuals who think big and want to define the world of tomorrow. At Amazon, you will grow into the high-impact, visionary person you know you’re ready to be. Every day will be filled with exciting new challenges, developing new skills, and achieving personal growth.

About the Internship

Do you love building tools and data pipelines? Are you excited by the opportunity to create clear, effective reports and data visualizations, and collaborate with stakeholders to answer 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?

Amazon is looking for a Data Engineer Intern to join one of 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 with a manager and a mentor. You will have the opportunity to affect 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.

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 summer and learn in a real-world setting.

Key Job 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 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.
• Work collaboratively with Business Analysts, Data Scientists, and other internal partners to identify opportunities/problems.
• Provide assistance to the team with troubleshooting, researching the root cause, and thoroughly resolving defects in the event of a problem.

A Day in the Life

Our Data Engineers build and maintain the infrastructure to answer questions with data, using software engineering best practices, data management fundamentals, data storage principles, and recent advances in distributed systems (e.g., MapReduce, MPP architectures, NoSQL databases).

About the Team

If you’re insatiably curious and always want to learn more, then you’ve come to the right place.

Benefits

• Competitive pay
• Impactful project and internship/role deliverables
• Hybrid working (team dependent)
• Networking opportunities with fellow interns
• Internship events such as speaker series, intern panels, Leadership Principles sessions, Amazon writing skills sessions.
• Mentorship and career development

Future Opportunities

If you’re successful during your internship, you could be considered for a graduate role after finishing your university studies.

Internship Details

• Internship start dates vary throughout the year.
• Ideal internship length is 6 months.

Basic Qualifications

• Currently enrolled in a Bachelor’s or Master´s degree program in computer engineering, computer science, or a similar technical field.
• Advanced knowledge and/or experience using SQL.
• Experience with data querying or modeling with SQL, Excel.
• Experience with a scripting language (e.g., Python, Java, or R).
• Knowledge of BI analytics/reporting/visualization tools (e.g., Tableau, AWS QuickSight, COGNOS, or other third-party tools).

Preferred Qualifications

• Master’s or advanced technical degree.
• Proficient in at least one or more query languages, schema definition languages, and scripting languages.
• Knowledge of writing and optimizing SQL queries in a business environment with large-scale, complex datasets.
• Experience with data visualization software (e.g., AWS QuickSight or Tableau) or open-source projects.
• Experience with big data processing technology (e.g., Hadoop or Apache Spark), data warehouse technical architecture, infrastructure components, ETL, and reporting/analytic tools and environments.
• Ability to deal with ambiguity in a fast-paced environment.