Data Engineer, Early Career - 2026 (CAN)

NOTE: By applying to this position, your application will be considered for Toronto, ON to start in November or December 2026.

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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? A career 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.

This is a full-time position, meaning candidates 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.

Key job responsibilities
As a Data Engineer, 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
We’re on the lookout for the curious, those who think big and want to define the world of tomorrow. Every day will be filled with exciting new challenges, developing new skills, and achieving personal growth.
How often can you say that your work changes the world? At Amazon, you’ll say it often. Join us and define tomorrow.