Sr. Data Engineer – Amazon – Vancouver, BC
Location: Vancouver, BC | Company: Amazon
Vancouver’s tech scene is home to some of Amazon’s most ambitious teams, and the WW Pricing Data and Insights group is no exception. If you’re a seasoned Senior Data Engineer who thrives on large-scale data challenges and wants to shape how billions of pricing decisions are made across Amazon’s global marketplace, this role at Amazon Development Centre Canada ULC in Vancouver, BC is worth your attention.
This isn’t your typical data engineering position. You’ll be a technical lead within a team that sits at the heart of Amazon Retail and third-party pricing, building ML data infrastructure, designing next-generation data pipelines, and leveraging GenAI to develop cutting-edge analytics solutions that directly influence customer and seller experiences worldwide.
About the Role: Sr. Data Engineer, WW Pricing Data and Insights
As a Senior Data Engineer on the WW Pricing Data & Analytics team, you’ll take technical ownership of the data models and processes that power Amazon’s pricing algorithms. You’ll work alongside Data Engineers and Business Intelligence Engineers, leading architectural design decisions and mentoring colleagues on engineering best practices. Your work directly feeds the systems that price and publish millions of products every single day.
Collaboration is central to this position. You’ll interface with multiple technology teams to extract, transform, and load data from diverse sources, manage AWS cloud resources, and continuously improve reporting and analysis processes to better serve internal customers and business stakeholders. The ability to balance technical depth with cross-functional communication is essential here.
Benefits and Salary
The base salary range for this position in Vancouver, BC is $135,700 to $226,500 CAD annually. As part of Amazon’s total compensation approach, the package may also include sign-on payments and Restricted Stock Units (RSUs), with final compensation determined by experience, qualifications, and location. Amazon provides a comprehensive benefits package including health insurance (medical, dental, vision, prescription, and basic life & AD&D), a Registered Retirement Savings Plan (RRSP), Deferred Profit Sharing Plan (DPSP), paid time off, and additional resources supporting health and well-being.
Job Details
🏢 Company: Amazon Development Centre Canada ULC
📍 Location: Vancouver, BC
🆔 Job ID: 10514189
💰 Pay: $135,700 – $226,500 CAD annually
Responsibilities
In this role, your day-to-day work will span architecture, development, and mentorship. You’ll be accountable for the end-to-end quality of data pipelines and BI solutions, while also guiding the technical direction of the broader team. These responsibilities are foundational to Amazon’s ability to deliver competitive pricing at a global scale.
- Architect and implement next-generation data pipelines and business intelligence solutions that support pricing at scale
- Build GenAI-powered data and analytics solutions to advance the team’s next-generation capabilities
- Manage AWS resources including EC2, RDS, Redshift, Kinesis, EMR, and Lambda to ensure system reliability and performance
- Design and deliver high-quality data architecture and pipelines supporting business analysts, data scientists, and customer reporting needs
- Extract, transform, and load data from a wide variety of sources by collaborating with cross-functional technology teams
- Automate and simplify ongoing reporting and analysis processes to improve self-service support for internal customers
- Mentor team members on engineering best practices and provide technical leadership across the team
Requirements / Skills
The right candidate brings deep hands-on experience in data engineering and is comfortable working with extremely large and complex datasets. Amazon values engineers who can both build robust systems and communicate technical concepts clearly to diverse stakeholders. Leadership qualities and a genuine interest in pricing data and analytics will set strong candidates apart.
- 5+ years of data engineering experience with a track record of delivering scalable solutions
- Data modelling, warehousing, and ETL pipeline development experience
- SQL proficiency for querying and transforming large datasets
- Modern scripting or programming language experience — Python, Java, Scala, or NodeJS
- Experience mentoring team members and establishing engineering best practices
- Big data technologies such as Hadoop, Hive, Spark, or EMR (preferred)
- Experience operating large data warehouses in production environments (preferred)
- Bachelor’s degree or above in econometrics, statistics, industrial engineering, operations research, data mining, analytics, or a related quantitative field — or equivalent experience with GenAI model benchmarking (preferred)
How to Apply
To apply, visit the official job posting using the link below. Make sure your resume is up to date before submitting your application.
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Job Summary & Tips for Applying
Quick Summary & What to Highlight: This Sr. Data Engineer role at Amazon in Vancouver is perfect for candidates who excel in data pipeline architecture, ETL development, and cloud-based data engineering on AWS. On your resume, emphasize any experience with large-scale data warehousing, attention to detail in data modelling, and your ability to work in a fast-paced, high-impact environment. If you’ve previously worked in pricing systems, e-commerce data, or ML data infrastructure, 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, AWS Redshift, and GenAI analytics that appear in the posting. Quantify your achievements where possible (e.g., “designed pipelines processing 10M+ records daily” or “reduced data latency by 40% through pipeline optimisation”). Write a brief cover letter expressing your genuine interest in Amazon‘s pricing data challenges and why you’re excited about this opportunity in Vancouver. 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 developments in their pricing technology, and the company’s focus on customer trust beforehand. Prepare specific examples using the STAR method (Situation, Task, Action, Result) to demonstrate your technical leadership and data engineering expertise. Common questions may include scenarios about designing scalable systems, mentoring junior engineers, and handling ambiguous data problems. Dress appropriately for a technology environment, arrive 10–15 minutes early for in-person or log on early for virtual interviews, and bring copies of your resume. Prepare thoughtful questions about the team’s roadmap, current data infrastructure, and GenAI initiatives. After the interview, send a thank-you email within 24 hours reiterating your interest in the position.
