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Forma.ai

Staff Back End Engineer (Data Platform)

Toronto, ON, Canada

Full-time

Apply About employer

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Job details

Job type: Full-time
Apply by: Jan 27, 2027
Posting language: English
Posted: Nov 3, 2026

Original job description

About Forma.ai:

Forma.ai is a Series B startup that's revolutionizing how sales compensation is designed, managed and optimized. We handle billions in annual managed commissions for market leaders like Edmentum, Stryker, and Autodesk.

Our growth has been fuelled by our passion for fundamentally changing and shaping how companies use sales intelligence to drive business strategy.

We’re welcoming equally driven individuals who are excited about creating something big!

About the Team

Engineers on this team construct our rules-based calculating engine for processing sales commissions. This might sound simple if you have never been exposed to sales comp plans, it is not! We are low on meetings, high on accountability. Most of the team are in EST time zone but we have a few located in PST and Central as well. We are far from maintenance / progressive evolution in many areas, there is a lot of room to make a big impact in the overall design.

What you’ll be doing

Reporting to the Manager of Data Platform, you will play a critical role in the evolution of our Spark based data platform. You'll lead development efforts for our complex, data-rich platform features while being an example to the team of code quality and thoughtful software design. You will be working on the most challenging code at Forma.

As a Staff Engineer, you are expected to operate with a high degree of ownership and trust. This includes proactively identifying architectural risks, surfacing edge cases or constraints others may not see, and advocating for improvements that strengthen the long-term integrity of the system. We value engineers who bring forward thoughtful perspectives - even when they challenge assumptions - and who help the team see around corners.

You will:

Design and evolve backend services that power product workflows.
Architect data models representing hierarchical & graph structures, relationships, and large-scale enterprise datasets.
Build deterministic, reliable systems that allow customers to reason clearly about their data.
Drive architectural decisions that balance extensibility, performance, and operational simplicity.
Improve observability, testing strategy, and production reliability across backend services.
Partner closely with Product to translate nuanced business requirements into clean, scalable designs.
Mentor engineers across levels and help raise the bar for backend engineering standards.
Use, and demonstrate using, AI tooling to improve implementation velocity while thoughtfully investing in technical and product specifications

What We're Looking for:

Significant experience designing and building complex backend systems in production environments.
Demonstrated ability to surface unarticulated risks, propose alternative approaches, and advocate for architectural improvements with sound technical reasoning.
Expertise in at least one production-grade backend language (e.g., Python, Java, Kotlin, Go, C#, etc.).
Strong foundation in relational schema design, data modelling, and SQL.
Background working with Spark, or other ETL tools / frameworks
Experience working with hierarchical, graph-like, or relationship-heavy data structures.
Familiarity with graph databases or graph-based modelling concepts is a strong plus.
Excellent written and verbal communication skills.
A track record of improving scalability, reliability, and observability in distributed or data-intensive systems.
A desire to influence architecture and product direction - not just implement tickets.
Thrive in a collaborative, detail-oriented environment across Engineering, Product, and Analytics.

Nice to have:

Experience building SaaS products serving mid-market or enterprise customers.
Experience building rule-driven systems, validation workflows, or approval/governance platforms.
Familiarity with AWS-based infrastructure and Kubernetes.
Exposure to Sales Performance Management (SPM), RevOps, Incentive Compensation (ICM), or related domains. ****

Technologies we use

Frontend: JavaScript, React, TypeScript

Backend: Java/Springboot, Django, Postgres

Infrastructure: AWS, Docker

What success looks like: 30/60/90 daysFirst 30 days

You’ll focus on building deep context across the product domain, backend architecture, and the data models that power Forma’s platform.

By the end of your first 30 days, you will have:

Developed a strong understanding of Forma.ai’s product, customers, and sales performance domain.
Built a clear mental model of the backend architecture, core services, and data flows across the system.
Gained familiarity with key data models, including hierarchical structures, relationships, and workflow-driven entities.
Set up your development environment and become comfortable navigating the codebase, services, and infrastructure.
Learned the team’s engineering practices around testing, observability, deployment, and reliability.
Built relationships with engineering, product, and analytics partners.
Contributed to technical discussions, asking thoughtful questions and identifying early areas of complexity or risk.
Shipped small but meaningful improvements or fixes to build familiarity with the system.
Started identifying opportunities to improve data modeling, system clarity, or backend reliability.

First 60 days

You’ll begin owning meaningful backend systems and influencing technical decisions.

By the end of your first 60 days, you will have:

Taken ownership of a significant backend component, service, or workflow.
Designed and delivered well-structured, maintainable backend code aligned with system standards.
Partnered closely with Product to translate complex business requirements into scalable backend designs.
Demonstrated strong judgment in data modeling, especially around relationships, hierarchy, and workflow representation.
Identified and surfaced architectural risks, edge cases, or inconsistencies in existing systems.
Proposed and, where appropriate, implemented improvements to backend architecture, data models, or service boundaries.
Contributed to improvements in observability, testing, and production reliability.
Participated actively in code reviews and technical design discussions, raising the bar for quality and clarity.
Begun mentoring or supporting other engineers in areas of strength.
Built enough system context to make informed tradeoffs between performance, extensibility, and simplicity.

First 90 days

You’ll be operating as a trusted technical leader across backend systems.

By the end of your first 90 days, you will have:

Led the design and delivery of a complex backend initiative spanning multiple services or domains.
Introduced or significantly improved core data models, system architecture, or workflow handling.
Demonstrated the ability to anticipate and mitigate long-term architectural risks.
Influenced technical direction through clear, well-reasoned proposals and design decisions.
Improved the reliability, observability, or scalability of critical backend systems.
Established strong working relationships across Engineering, Product, and Analytics.
Elevated engineering standards through mentorship, design reviews, and technical guidance.
Helped the team better reason about complex, data-intensive workflows through clearer system design.
Identified and begun executing on longer-term backend investments that improve system integrity and developer velocity.
Demonstrated clear impact on both system quality and the team’s ability to deliver confidently at scale.

Additional Job Info:

This position is for an existing vacancy

What you can expect from us

Meaningful compensation. In addition to your base salary, you’ll join our employee stock ownership plan to further recognize your contributions to Forma.ai’s success.

Healthcare coverage. We have a full benefits package that includes medical, dental, vision, disability and life insurance, and a paid parental leave program.

Learning and development. Access the resources you want to help you grow in your role by utilizing our $750 yearly training stipend.

Growth. You’ll have a huge opportunity to build a career for yourself and gain the type of experience you’re looking for, whether that’s as an individual contributor or as a people leader.

Our Values:

Work well, together. We’re real. We have kids and pets. Mortgages and student loans. We’re in this together, so no matter how brilliant any one of us is, we always play nice with one another – no exceptions.
Be precise. Be relentless. We believe complacency breeds failure, so we set new goals as quickly as we achieve them. We persist in the face of adversity, learn from our mistakes, and push each other to continuously improve. The status-quo is kryptonite.
Love our tech. Love our customers. Our platform solves a very complex problem in a currently underserved market. While everyone at Forma isn’t customer-facing, we’re all customer-focused. Maybe even slightly customer-obsessed.

Use of AI for Recruitment

Currently, Forma.ai does not use artificial intelligence as part of our recruitment process, specifically but not limited to the screening, filtering and shortlisting of applicants.

Our commitment to you:

Forma is a proud equal opportunity employer that is committed to creating a diverse and inclusive work environment. Every effort to accommodate candidates for accessibility will be made upon request. Information received related to accommodations will be addressed confidentially. We know that applying to a new role takes a lot of effort. You're encouraged to apply even if your experience doesn't precisely match the job description. There are many paths to a successful career and we’re looking forward to reading yours.

We thank all candidates for their interest however only qualified applicants will be shortlisted.

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More about this job

Responsibilities

Design and evolve backend services and data models for Forma.ai’s Spark-based platform, delivering reliable, scalable systems for complex enterprise data and workflows. Lead architectural decisions, improve testing, observability, and production reliability, partner with Product, and mentor engineers.

Requirements

Candidates should have significant experience building complex production backend systems, strong skills in a production-grade programming language, SQL, relational schema design, and data modeling, plus experience with Spark or other ETL frameworks. They should be able to identify architectural risks, improve scalability and reliability, communicate effectively, and influence technical direction; experience with graph-like data, SaaS, AWS, Kubernetes, or sales compensation domains is advantageous.

Skills

Backend System Design
Python
Java
Kotlin
Go
C#
SQL
Relational Schema Design
Data Modeling
Apache Spark
ETL
Graph Data Modeling
Distributed Systems
Observability
System Reliability
Technical Mentorship

Benefits

Employee Stock Ownership Plan
Medical Insurance
Dental Insurance
Vision Insurance
Disability Insurance
Life Insurance
Paid Parental Leave
Annual Training Stipend

Visa sponsorship

Not detected in the job text

Keywords

Backend Engineering
Data Platform
Apache Spark
Java
Spring Boot
Python
Django
PostgreSQL
SQL
AWS
Docker
Kubernetes
ETL
Data Modeling
Relational Schema Design
Hierarchical Data
Graph Data Modeling
Distributed Systems
Enterprise SaaS
Sales Compensation
Sales Performance Management
Incentive Compensation
Revenue Operations
Observability
Testing
Production Reliability
System Architecture
Workflow Validation
AI Tooling
Technical Mentorship

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