Senior Back End Engineer (Data Platform)

Forma.ai•Toronto, ON

2d•CA$150,000 - CA$190,000•Hybrid

About The Position

Forma.ai is a Series B startup revolutionizing sales compensation. The Engineering team builds our rules-based calculation engine for processing sales commissions. This role is focused on the evolution of our Spark-based data platform, designing and building data-rich platform capabilities, contributing to system design discussions, and ensuring data systems remain reliable, maintainable, and scalable. The Senior Engineer, Data Platform is expected to operate with strong ownership and sound technical judgment, identifying risks, surfacing edge cases, asking thoughtful questions, and proposing improvements. Key activities include designing, building, and improving Spark-based data pipelines and platform services, working with complex data models, building reliable data systems, improving testing, observability, data quality, and production reliability, partnering with Product, Engineering, and Analytics to translate business requirements into scalable data designs, participating in design and code reviews, and using AI tooling to improve delivery speed.

Requirements

Strong experience building data systems or backend systems in production.
Experience with Spark or similar data processing / ETL frameworks.
Proficiency in at least one production-grade language such as Python, Java, Scala, Kotlin, Go, C#, or similar.
Strong SQL, relational schema design, and data modeling skills.
Experience with large-scale, hierarchical, graph-like, relationship-heavy, or workflow-driven datasets.
Ability to reason through technical tradeoffs, identify risks, and propose practical improvements.
Experience improving scalability, reliability, observability, or maintainability in data-intensive systems.
Strong communication skills and comfort collaborating across Engineering, Product, and Analytics.

Nice To Haves

Experience building SaaS products for mid-market or enterprise customers.
Experience with rule-driven systems, validation workflows, calculation engines, or approval/governance platforms.
Familiarity with AWS-based infrastructure and Kubernetes.
Familiarity with graph databases or graph-based modeling concepts.
Exposure to Sales Performance Management, RevOps, Incentive Compensation, or related domains.

Responsibilities

Design, build, and improve Spark-based data pipelines and platform services.
Work with complex data models representing sales compensation plans, hierarchies, relationships, and enterprise datasets.
Build reliable, deterministic data systems that customers and internal teams can trust.
Improve testing, observability, data quality, and production reliability across the systems you work on.
Partner with Product, Engineering, and Analytics to translate complex business requirements into scalable data designs.
Participate in design reviews, code reviews, technical discussions, and knowledge sharing.
Use AI tooling to improve delivery speed while maintaining strong engineering standards.