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Software Development Engineer, Measurement, Ad Tech, and Data Science (MADS)

Amazon

Software Development Engineer, Measurement, Ad Tech, and Data Science (MADS)

Amazon

Toronto, ON, CAN

·

On-site

·

Full-time

·

1mo ago

Compensation

CA$114,800 - CA$191,800

Benefits & Perks

Wellness benefits

Top Tier compensation with equity

Flexible PTO policy

Remote work flexibility

Health, dental, and vision coverage

Learning and development stipend

Required Skills

Apache Spark

SQL

PyTorch

Join our dynamic Reach Planning Engineering team within Measurement Ad Tech Data Science to build the next generation of advertising technology at Amazon. In this role, you'll own, design, and deliver highly scalable systems that empower advertisers to plan campaigns and build strategies related to reach and other media planning capabilities.
You'll work on our full-service, full-stack advertising platform, specifically developing APIs and AI Agents that deliver Amazon signals to improve planning for advertisers and enhance campaign impact. This position offers the opportunity to solve complex problems at scale while working across Amazon's advertising ecosystem to create solutions that drive meaningful business results for our advertising customers.

  • Key job responsibilities
  • Design and implement scalable, high-performance systems that power Amazon's advertising platform, ensuring robust functionality and optimal user experience
  • Provide meaningful code reviews to team members and actively participate in the full software development lifecycle including scoping, design, implementation, testing, deployment, and maintenance
  • Own operational excellence for your systems, proactively identifying root causes of issues and implementing permanent solutions that improve reliability and performance
  • Work closely with stakeholders across Amazon to understand business needs and customer value, translating requirements into technical solutions that enhance advertiser campaign effectiveness
  • Develop innovative APIs and AI-powered solutions that leverage Amazon's unique signals to optimize ad planning and delivery, contributing to the growth of Amazon's advertising business
    A day in the life
    As part of the Reach Planning Engineering team, you'll start your day collaborating with data scientists and product managers to define requirements for new API features that improve media planning. You'll write code, participate in design discussions, and review pull requests from teammates. Throughout the day, you'll analyze system performance, troubleshoot issues, and optimize algorithms that power our AI Agents. You'll also connect with internal and external partners to gather feedback on how our tools are performing and identify opportunities for enhancement.

Basic Qualifications

  • 3+ years of non-internship professional software development experience
  • 1+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
  • Experience programming with at least one software programming language

Preferred Qualifications

  • 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
  • Bachelor's degree in computer science or equivalent
  • Experience working with GenAI-powered development tools and agentic AI assistants (e.g., code generation, AI-assisted debugging, automated testing, and documentation tools) to enhance software development productivity and code quality
    Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
    Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

The base salary range for this position is listed below. As a total compensation company, Amazon's package may include other elements such as sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon offers comprehensive benefits including health insurance (medical, dental, vision, prescription, basic life & AD&D insurance), Registered Retirement Savings Plan (RRSP), Deferred Profit Sharing Plan (DPSP), paid time off, and other resources to improve health and well-being. We thank all applicants for their interest, however only those interviewed will be advised as to hiring status.

CAN, ON, Toronto - 114,800.00 - 191,800.00 CAD annually

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About Amazon

Amazon

Amazon

Public

Amazon.com, Inc. is an American multinational technology company engaged in e-commerce, cloud computing, online advertising, digital streaming, and artificial intelligence.

10,001+

Employees

Seattle

Headquarters

Reviews

2.9

10 reviews

Work Life Balance

2.8

Compensation

3.7

Culture

2.5

Career

2.3

Management

2.1

35%

Recommend to a Friend

Pros

Good pay and compensation

Strong benefits package

Flexible scheduling options

Cons

Poor management and leadership

Limited growth and promotion opportunities

High stress and demanding work environment

Salary Ranges

2 data points

L2

L3

L4

L5

L6

L2 · Cybersecurity Analyst L2

0 reports

$234,132

total / year

Base

$93,653

Stock

$117,066

Bonus

$23,413

$163,892

$304,372

Interview Experience

10 interviews

Difficulty

3.7

/ 5

Duration

21-35 weeks

Offer Rate

20%

Experience

Positive 10%

Neutral 10%

Negative 80%

Interview Process

1

Application Review

2

Recruiter Screen

3

Online Assessment

4

Technical Phone Screen

5

Onsite/Virtual Loop

6

Team Matching

7

Offer

Common Questions

Coding/Algorithm

System Design

Behavioral/STAR

Leadership Principles

Technical Knowledge