Software Engineer - Retailer Growth

Faire•Toronto, ON

1d•CA$129,500 - CA$178,000•Hybrid

About The Position

At Faire, we have a business unit focused on Retailer Growth that oversees core growth strategies from top of funnel, to onboarding, to helping Retailers get up and running to be successful on Faire. As a Software Engineer on the Retailer Growth pillar, you will work closely with product, design, data science, and marketing to build and scale the systems that power our growth - from experimentation and personalization to onboarding and lifecycle engagement. This is a generalist role. We’re looking for engineers who are curious, product-minded, and excited to work across the stack to drive business outcomes.

Requirements

3+ years of software engineering experience.
Comfortable working across the stack — experience with frontend (TypeScript, React) and/or backend (Kotlin, Java) is welcome.
Experience shipping features end-to-end, from design through production.
Familiarity with experimentation concepts (A/B testing, feature flags, traffic allocation).
Ability to work with data: comfortable reading dashboards, writing queries, and reasoning about metrics.
Strong product instincts — you think about the user and the business, not just the implementation.
A bachelor’s degree in Computer Science/Software Engineering or equivalent industry experience.
A love for technology, and an insatiable curiosity for new tools to solve real problems.

Nice To Haves

Experience in a growth, lifecycle, or consumer product environment is a plus.

Responsibilities

Collaborate closely with product managers, designers, data scientists, and marketing to ship features and experiments that drive retailer acquisition, onboarding, and engagement.
Independently execute end-to-end projects — from scoping and design through implementation and measurement.
Build and contribute to growth infrastructure: experimentation tooling, targeting and segmentation systems, lifecycle triggers, and personalization features.
Design and implement reliable, observable, and scalable services and APIs that operate at marketplace scale.
Use data to drive decisions: partner with Analytics and Data Science to instrument features, design experiments, and interpret results.
Optimize user-facing experiences for performance and conversion, with attention to the full funnel.
Contribute to a culture of quality: write clean, well-tested code and share knowledge across the team.