Forma.ai - Staff Back End Engineer (Data Platform)

• 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. **** • Technologies we use • Frontend: JavaScript, React, TypeScript • Frontend: • Backend: Java/Springboot, Django, Postgres • Backend: • Infrastructure: AWS, Docker • Infrastructure: • What success looks like: 30/60/90 days • First 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.