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Quality Assurance Specialist
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Spécialiste principal national du support technique et de l'impression industrielle (Canada)
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5% - Lead referrals and product promotion to existing customers

Braze

Senior Software Engineer II, Decisioning Studio Integrations Team

Toronto, ON, Canada

Full-time

Apply About employer

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Job details

Job type: Full-time
Apply by: Nov 20, 2026
Experience: 6+ years of backend engineering experience building and operating distributed systems in production
Posting language: English
Posted: Oct 21, 2026

Original job description

At Braze, we have found our people. We’re a genuinely approachable, exceptionally kind, and intensely passionate crew.

We seek to ignite that passion by setting high standards, championing teamwork, and creating work-life harmony as we collectively navigate rapid growth on a global scale while striving for greater equity and opportunity – inside and outside our organization.

To flourish here, you must be prepared to set a high bar for yourself and those around you. There is always a way to contribute: Acting with autonomy, having accountability and being open to new perspectives are essential to our continued success.

Our deep curiosity to learn and our eagerness to share diverse passions with others gives us balance and injects a one-of-a-kind vibrancy into our culture.

If you are driven to solve exhilarating challenges and have a bias toward action in the face of change, you will be empowered to make a real impact here, with a sharp and passionate team at your back. If Braze sounds like a place where you can thrive, we can’t wait to meet you.

WHAT YOU'LL DO

We're looking for a Senior Software Engineer II to join the Decisioning Studio Integrations team building BrazeAI Decisioning Studio™. Decisioning Studio is a reinforcement learning platform that runs continuous experiments to personalize customer engagement for each individual. Its results depend on the data it learns from and on the channels that carry its decisions to customers. Our team owns both. We ingest enterprise customer data of any schema and at a very large scale from warehouses, engagement platforms and other enterprise systems. We also deliver the recommendations from our RL pipelines across email, SMS, push, in-app and other channels. These are high-impact, customer-facing features.

In this role, you will:

Lead complex integration projects from design through build and rollout, and set technical direction for the Decisioning Studio integration platform
Design and build integrations with cloud data warehouses, customer engagement platforms and other enterprise systems, for both data ingestion and activation orchestration
Build ingestion pipelines that handle every way customers send data, including batch pulls, file drops, APIs and streaming, and accept arbitrary schemas without letting bad data reach our models
Build event-driven, fault-tolerant activation pipelines that deliver recommendations on schedule, recover cleanly from partial failures and never send twice
Design for multi-region deployment and compliance requirements, including data residency and PII handling
Own your systems in production. Instrument them with Datadog, take part in the on-call rotation, and take incidents all the way to the root cause
Work with data scientists, ML engineers and product managers to turn integration requirements into reusable platform capabilities
Mentor engineers and raise the bar for code quality, testing and design review

WHO YOU ARE

6+ years of backend engineering experience building and operating distributed systems in production
A track record of technical leadership: owning complex projects end to end, making architecture decisions and setting direction for other engineers
Experience building data pipelines or integrations that move very large volumes of data between systems, including schema changes, backfills and partial failures
A strong grasp of event-driven architecture and reliability patterns: message brokers such as Kafka, idempotency, retries with backoff, dead-letter handling, and at-least-once versus exactly-once tradeoffs
Proficiency in Python and SQL
Hands-on experience with cloud infrastructure (GCP preferred) and Kubernetes
Experience with AI coding assistants, and the judgment to know when they help and when they don't
A clear communicator who works well with engineering, data science and product
A self-starter who finds problems and works around obstacles without waiting for direction

Bonus points:

Experience integrating with cloud data warehouses such as BigQuery, Snowflake or Redshift
Experience integrating with customer engagement platforms such as Braze, Adobe, Salesforce Marketing Cloud or Klaviyo
Experience building multi-region systems under data residency and compliance requirements
Experience running ML systems in production

For candidates based in Canada, the pay range for this position at the start of employment is expected to be between CA$186,838 and CA$334,740/year, with an expected On Target Earnings (OTE) between CA$205,600 and CA$366,000/year (including bonus or commission). Your exact offer may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. In addition to cash compensation, this role qualifies for a comprehensive Total Rewards package that includes equity grants of restricted stock (RSUs) so that you will own a piece of our company.

WHAT WE OFFER

Braze benefits vary by location, and we encourage you to review our specific benefits offerings for each country at here. More details on benefits plans will be provided if you receive an offer of employment.

From offering comprehensive benefits to fostering hybrid ways of working, we've got you covered so you can prioritize work-life harmony. Braze offers benefits such as:

Competitive compensation that may include equity
Retirement and Employee Stock Purchase Plans
Flexible paid time off
Comprehensive benefit plans covering medical, dental, vision, life, and disability
Family services that include fertility benefits and equal paid parental leave
Professional development supported by formal career pathing, learning platforms, and a yearly learning stipend
A curated in-office employee experience, designed to foster community, team connections, and innovation
Opportunities to give back to your community, including an annual company-wide Volunteer Week and donation matching
Employee Resource Groups that provide supportive communities within Braze
Collaborative, transparent, and fun culture recognized as a Great Place to Work®

ABOUT BRAZE

Braze is the leading customer engagement platform that empowers brands to Be Absolutely Engaging™ Braze helps brands deliver great customer experiences that drive value both for consumers and for their businesses. Built on a foundation of composable intelligence, BrazeAI™ allows marketers to combine and activate AI agents, models, and features at every touchpoint throughout the Braze Customer Engagement Platform for smarter, faster, and more meaningful customer engagement. From cross-channel messaging and journey orchestration to Al-powered decisioning and optimization, Braze enables companies to turn action into interaction through autonomous, 1:1 personalized experiences.

The company has repeatedly been recognized as a Leader in marketing technology by industry analysts, and was voted a G2 “Best of Marketing and Digital Advertising Software Product” in 2025.

Braze was also named a 2025 Best Companies To Work For by U.S. News and World Report, a 2025 America’s Greatest Companies by Newsweek, and a 2025 Fortune Best Workplace in Technology™ by Great Place To Work®, among other accolades. Braze is also proudly certified as a Great Place to Work® in the U.S., the UK, Australia, and Singapore.

The company is headquartered in New York with offices in Austin, Berlin, Bucharest, Chicago, Dubai, Jakarta, London, Paris, San Francisco, São Paulo, Singapore, Seoul, Sydney and Tokyo.

BRAZE IS AN EQUAL OPPORTUNITY EMPLOYER

At Braze, we strive to create equitable growth and opportunities inside and outside the organization.

Building meaningful connections is at the heart of everything we do, and that includes our recruiting practices. We're committed to offering all candidates a fair, accessible, and inclusive experience – regardless of age, color, disability, gender identity, marital status, maternity, national origin, pregnancy, race, religion, sex, sexual orientation, or status as a protected veteran. When applying and interviewing with Braze, we want you to feel comfortable showcasing what makes you you.

We know that sometimes different circumstances can lead talented people to hesitate to apply for a role unless they meet 100% of the criteria. If this sounds familiar, we encourage you to apply, as we’d love to meet you

OUR AI-POWERED BRAZE RECRUITMENT PROCESS

At Braze, we’re committed to a fair and transparent candidate experience. To help our recruitment teams focus on what matters most - the person behind each application - we use AI-assisted tools at certain stages of our recruitment process.

This includes using AI to analyze the experience, skills and qualifications in your application materials to help with screening and prioritizing candidates. Such screening may amount to a form of solely automated decision-making. We also use AI for administrative support, like scheduling and recording interviews and summarizing interview notes. Our recruiting teams remain responsible for all hiring decisions and are involved throughout the process.

Depending on where you are located, you may have certain rights available to you in relation to Braze’s use of AI:

To opt out of AI-assisted review of your application, please click the “Learn More” at the end of the application form below and follow the instructions before submitting your application. Please note, if you apply to multiple roles at Braze, you will need to opt out in relation to each application.
To exercise other types of rights, such as rights to request further information about how AI is used in our recruitment process, to request a manual review of any decision made or to contest a decision, please contact us at talentdata.privacy@braze.com.

Please contact us at talentdata.privacy@braze.com with any questions. To find out more about our hiring process, check out this page.

Notice Regarding Automated Employment Decision Tool (NYC Local Law 144)

Our use of AI during the application review process may include the use of automated employment decision tools. Pursuant to New York City Local Law 144, for roles based in New York City, or if you reside in New York City, you have the right to request an alternative selection process or a reasonable accommodation instead of AI-assisted review.

To opt out of AI-assisted review of your application, please click the “Learn More” button below and follow the instructions before submitting your application. Please note, if you apply to multiple roles at Braze, you will need to opt out in relation to each application. Please submit any other request to our Talent Acquisition team at talentdata.privacy@braze.com promptly after applying. Summaries of the most recent bias audit results for such tools are available here.

Please see our Candidate Privacy Policy for more information on how Braze processes your personal information during the recruitment process and, if applicable based on your location, how you can exercise any privacy rights.

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More about this job

Responsibilities

Lead integration projects and set technical direction for the Decisioning Studio platform, building large-scale data ingestion and reliable recommendation activation integrations across enterprise systems and customer channels. Operate production systems, including monitoring, on-call incident response, compliance-aware multi-region design, and mentoring engineers.

Requirements

Requires 6+ years of backend engineering experience operating distributed systems, with a record of technical leadership and experience building high-volume data pipelines or integrations. Candidates should be proficient in Python and SQL, understand event-driven reliability patterns, and have hands-on cloud infrastructure and Kubernetes experience; GCP is preferred.

Skills

Backend Engineering
Distributed Systems
Technical Leadership
Data Pipelines
System Integrations
Event-Driven Architecture
Reliability Engineering
Python
SQL
Cloud Infrastructure
Google Cloud Platform
Kubernetes
Kafka
Multi-Region Systems
Machine Learning Systems
Datadog

Benefits

Equity Grants
Retirement Plan
Employee Stock Purchase Plan
Flexible Paid Time Off
Medical Insurance
Dental Insurance
Vision Insurance
Life Insurance
Disability Insurance
Fertility Benefits
Paid Parental Leave
Professional Development
Learning Stipend
Volunteer Opportunities
Donation Matching
Employee Resource Groups

Visa sponsorship

Not detected in the job text

Keywords

BrazeAI Decisioning Studio
Reinforcement Learning
Backend Engineering
Distributed Systems
Data Ingestion
Activation Orchestration
Data Pipelines
Batch Processing
File Drops
APIs
Streaming
Schema Evolution
Backfills
Event-Driven Architecture
Kafka
Idempotency
Retries With Backoff
Dead-Letter Handling
At-Least-Once Delivery
Exactly-Once Delivery
Python
SQL
Google Cloud Platform
Kubernetes
Datadog
Multi-Region Deployment
Data Residency
PII Handling
BigQuery
Snowflake

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