Data Engineer I – Amazon – Toronto, ON
Location: Toronto, ON | Company: Amazon
Amazon Business is reshaping B2B eCommerce from the ground up, and the team behind it is looking for a sharp Data Engineer I to join its Ops Analytics group in Toronto, Ontario. This is an early-stage team with real influence over the direction of a global B2B supply chain — a rare chance to shape something meaningful from within one of the world’s most ambitious tech companies.
In this role, you’ll be at the intersection of data architecture, pipeline development, and cross-functional collaboration. Your work will directly support the data infrastructure powering Amazon Business’s rapid growth, touching everything from bulk and pallet delivery operations to ML/AI model development for business customers across North America.
About the Role: Data Engineer I
As a Data Engineer I on the Amazon Business Ops Analytics team, you’ll be designing and building the systems that keep data flowing cleanly and reliably across a complex supply chain ecosystem. You’ll own the development of scalable data pipelines, contribute to the team’s technical road map, and work closely with partners across data engineering, software development, research, and modelling teams. The environment moves quickly and rewards ownership and initiative.
Beyond the technical work, this role requires someone who can build strong working relationships across cross-functional teams and adapt to shifting priorities in a goal-oriented, collaborative culture. You’ll be expected to contribute to how the team approaches data strategy, not just execute on it.
Benefits and Salary
The base salary range for this position is $80,700 to $134,800 CAD annually. Total compensation at Amazon may also include sign-on payments and Restricted Stock Units (RSUs), with final offers determined by experience, qualifications, and location. Amazon’s benefits package includes health insurance (medical, dental, vision, prescription, and basic life and AD&D), a Registered Retirement Savings Plan (RRSP), a Deferred Profit Sharing Plan (DPSP), paid time off, and additional resources to support health and well-being.
Job Details
🏢 Company: Amazon
📍 Location: Toronto, ON
🆔 Requisition ID: 10474520
💰 Pay: $80,700 – $134,800 CAD annually
Responsibilities
The day-to-day work of a Data Engineer I at Amazon Business centres on building and maintaining the data systems that underpin critical supply chain decisions. Your contributions will directly influence the reliability and scalability of data platforms used by teams across the globe.
- Design and develop data architecture, data standards, and end-to-end scalable data applications and pipelines
- Build and support data warehouse and data lake platforms for data analyses, ML/AI model development, validation, and implementation
- Develop collaborative relationships with key partners across data engineering, software development, research, modelling, and marketing teams
- Contribute to the team’s data strategy and technical road map for data storage and pipeline design
- Familiarise yourself quickly with a fast-paced environment and take ownership across a broad array of domains
Requirements / Skills
The ideal candidate is someone who’s comfortable taking ownership in ambiguous situations and thrives in a collaborative, results-driven setting. Amazon Business values technical depth combined with the ability to communicate clearly and build relationships across teams.
- 1+ years of data engineering experience in a professional setting
- Data modelling, warehousing, and ETL pipeline development experience
- Proficiency in one or more query languages such as SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, or Scala
- Experience with one or more scripting languages such as Python or KornShell
- Preferred: Experience with big data technologies including Hadoop, Hive, Spark, or EMR
- Preferred: Familiarity with ETL tools such as Informatica, ODI, SSIS, BODI, or Datastage
How to Apply
To apply, use the link below to access the official Amazon job posting. Make sure your resume is current and tailored to highlight your data engineering experience before submitting.
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Job Summary & Tips for Applying
Quick Summary & What to Highlight: This Data Engineer I role at Amazon in Toronto is ideal for candidates who excel in ETL pipeline development, data warehousing, and SQL or scripting languages. On your resume, emphasize any hands-on experience with data architecture and pipeline design, attention to detail in data quality, and your ability to work in a fast-paced, cross-functional environment. If you’ve previously worked in data engineering, analytics engineering, or a related technical role, make sure to highlight specific achievements and responsibilities that align with this position.
Resume & Application Tips: Before applying, tailor your resume to match the job description. Include keywords like ETL pipelines, data lake, and SQL that appear in the posting. Quantify your achievements where possible (e.g., “built pipelines processing 10M+ records daily” or “reduced data latency by 40%”). Write a brief cover letter expressing your genuine interest in Amazon Business and why you’re excited about this opportunity in Toronto. Double-check your application for spelling errors and ensure your contact information is current.
Interview Preparation: If selected for an interview, research Amazon‘s Leadership Principles, recent news about Amazon Business, and the team’s B2B supply chain focus beforehand. Prepare specific examples using the STAR method (Situation, Task, Action, Result) to demonstrate your data engineering and problem-solving skills. Common questions may include scenarios about handling large datasets, designing scalable systems, and cross-team collaboration. Dress appropriately for a technology environment, arrive 10–15 minutes early (or log in early for virtual interviews), and bring copies of your resume. Prepare thoughtful questions about the role, team dynamics, and growth opportunities. After the interview, send a thank-you email within 24 hours reiterating your interest in the position.
