Data Engineer, Advertising & Marketing Performance Intelligence
Amazon · Toronto, Canada · Software Development
mid
Data Engineer
ic
· Posted May 10, 2026
C$103,300 – C$172,600
CAD per year
Skills
About this role
Amazon is hiring a mid-level Data Engineer based in Toronto, Canada. The posting calls out experience with SQL, AWS, Serverless, Redshift. Compensation is listed at C$103,300–C$172,600 per year.
- Role
- Data Engineer
- Function
- data engineering
- Level
- mid
- Track
- Individual contributor
- Employment
- Full-time
- Location
- Toronto, Canada
- Department
- Software Development
- Posted
- May 10, 2026
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Job description
from Amazon careersThe Advertising & Marketing Performance Intelligence (AMPI) team is seeking passionate and talented senior Data Engineer to join us. The team is on a mission to create cohesive, relevant, and truly helpful marketing experiences for every advertiser through automated processes and intelligence that enable scaled personalization.
Key job responsibilities
Data Pipeline Development: Build and maintain end-to-end automated data pipelines using AWS technologies, SQL, and various APIs. Deliver solutions that are secure, maintainable, and capable of handling large-scale data processing while ensuring data quality and integrity.
Architecture & Design Contribution: Contribute to the design of scalable big data architectures by making sound technical trade-offs within established BAA standards. Identify and flag deficiencies in existing systems and propose improvements in collaboration with senior engineers.
Monitoring & Operational Excellence: Build and maintain monitoring systems including automated alarms. Support data access control mechanisms and help ensure compliance with security standards while maintaining data availability and consistency.
Performance Optimization: Evaluate and optimize data designs for scalability, latency, and performance within your area of ownership. Identify bottlenecks and implement efficient solutions that improve data exploration and experimentation workflows.
Technical Collaboration: Follow and advocate for engineering best practices across the team. Participate in design reviews, contribute to technical discussions, and work closely with cross-functional partners to deliver on shared goals.
Business Partnership: Serve as a knowledgeable point of contact for data structure and usage within your domain.
Key job responsibilities
Data Pipeline Development: Build and maintain end-to-end automated data pipelines using AWS technologies, SQL, and various APIs. Deliver solutions that are secure, maintainable, and capable of handling large-scale data processing while ensuring data quality and integrity.
Architecture & Design Contribution: Contribute to the design of scalable big data architectures by making sound technical trade-offs within established BAA standards. Identify and flag deficiencies in existing systems and propose improvements in collaboration with senior engineers.
Monitoring & Operational Excellence: Build and maintain monitoring systems including automated alarms. Support data access control mechanisms and help ensure compliance with security standards while maintaining data availability and consistency.
Performance Optimization: Evaluate and optimize data designs for scalability, latency, and performance within your area of ownership. Identify bottlenecks and implement efficient solutions that improve data exploration and experimentation workflows.
Technical Collaboration: Follow and advocate for engineering best practices across the team. Participate in design reviews, contribute to technical discussions, and work closely with cross-functional partners to deliver on shared goals.
Business Partnership: Serve as a knowledgeable point of contact for data structure and usage within your domain.
Basic Qualifications
This is an excerpt. Read the full job description on Amazon careers →