Forma.ai is hiring a Senior Back End Engineer (Data Platform)

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 build our rules-based calculation engine for processing sales commissions. This might sound simple if you have never been exposed to sales compensation plans, it is not. We are low on meetings and high on accountability. Most of the team is in the EST time zone, with a few located in PST and Central as well. We are still evolving many areas of the platform, which means there is meaningful room to improve the design, reliability, and scalability of the systems we build. What you’ll be doing Reporting to the Manager of Data Platform, you will play an important role in the evolution of our Spark-based data platform. You’ll design and build data-rich platform capabilities, contribute to system design discussions, and help ensure our data systems remain reliable, maintainable, and scalable as Forma grows. As a Senior Engineer, Data Platform, you are expected to operate with strong ownership and sound technical judgment. This includes identifying risks in the work you own, surfacing edge cases, asking thoughtful questions, and proposing improvements that strengthen the quality and reliability of the platform. You will: - 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. What we’re looking for - 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 have - 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. Technologies we use Frontend: JavaScript, React, TypeScript Backend: Java/Spring Boot, Django, Postgres Data Platform: Spark Infrastructure: AWS, Docker What success looks like: 30/60/90 days First 30 days You’ll focus on building context across Forma’s product domain, data platform, calculation engine, data models, and engineering practices. By the end of your first 30 days, you will have: - Set up your development environment and become comfortable navigating the codebase, data platform, services, and infrastructure. - Built a clear understanding of the product domain, Spark-based data flows, and key data models. - Learned the team’s practices around testing, observability, deployment, data quality, and reliability. - Built relationships with Engineering, Product, and Analytics partners. - Shipped small improvements or fixes to build familiarity with the system. First 60 days You’ll begin owning meaningful data platform work and contributing to technical decisions. By the end of your first 60 days, you will have: - Taken ownership of a data pipeline, platform component, workflow, or feature area. - Designed and delivered maintainable data platform code aligned with team standards. - Partnered with Product, Engineering, and Analytics peers to translate requirements into scalable data designs. - Identified risks, edge cases, data quality issues, or inconsistencies in the systems you work on. - Contributed to improvements in data modeling, pipeline reliability, testing, observability, or service boundaries. First 90 days You’ll be operating as a trusted senior contributor within the team. By the end of your first 90 days, you will have: - Designed and delivered a meaningful data platform initiative or major feature. - Improved important data models, Spark pipelines, platform services, or workflow handling. - Contributed to technical direction through clear, well-reasoned design decisions. - Improved the reliability, observability, scalability, or maintainability of data-intensive systems. - Helped the team deliver complex calculation and data workflows with greater confidence and clarity. Additional Job Info: - This position is for an existing vacancy - Salary Range: 150-190K CAD