Staff Back End Engineer (Data Platform)

Forma.ai•Toronto, ON

17h•Hybrid

About The Position

Forma.ai is a Series B startup revolutionizing sales compensation. The Data Platform team constructs the rules-based calculating engine for processing sales commissions. This role reports to the Manager of Data Platform and will play a critical role in the evolution of the Spark-based data platform. The engineer will lead development efforts for complex, data-rich platform features, setting an example for code quality and thoughtful software design. This role requires a high degree of ownership and trust, including proactively identifying architectural risks, surfacing edge cases, and advocating for system improvements. The team values engineers who bring forward thoughtful perspectives and help the team anticipate challenges.

Requirements

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.
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 Haves

Familiarity with graph databases or graph-based modelling concepts is a strong plus.
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.

Responsibilities

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.