Data Modelling Jobs in Toronto, ON (NOW HIRING)

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.

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

• 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.

• 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. ****

Frontend: JavaScript, React, TypeScript

Backend: Java/Springboot, Django, Postgres

Infrastructure: AWS, Docker

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.

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.

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.

• This position is for an existing vacancy