Staff Back End Engineer (Data Platform)

About the Company We are a rapidly growing Series B SaaS company transforming how organizations design, manage, and optimize sales compensation. Our platform processes billions of dollars in annual commission calculations for leading mid-market and enterprise organizations. Our growth is driven by a mission to fundamentally change how companies use sales intelligence and data to make better business decisions. We're looking for driven engineers who want to build meaningful technology and have a significant impact on a growing product. About the Team The engineering team builds and evolves a sophisticated rules-based engine responsible for calculating sales commissions at scale. While the problem may initially sound straightforward, sales compensation involves highly complex business rules, relationships, exceptions, and large volumes of data. The team operates with few meetings and a high degree of ownership and accountability. There is also significant opportunity to influence the architecture. Many areas of the platform are still evolving, meaning engineers can have a meaningful impact on system design, technical standards, and the long-term direction of the product. The Role As a Staff Backend Engineer, you will report to the Manager of Data Platform and play a key role in evolving a Spark-based data platform. You'll lead the development of complex, data-intensive platform capabilities while setting a high standard for software quality, architecture, and engineering practices. You will work on some of the most technically challenging areas of the platform. This role requires a high degree of ownership and trust. You'll be expected to identify architectural risks proactively, recognize edge cases and constraints, challenge assumptions when appropriate, and advocate for solutions that improve the long-term reliability and scalability of the system. What You'll Do

• Design and evolve backend services that support core product workflows.
• Architect data models representing hierarchical structures, relationships, and large-scale enterprise datasets.
• Build deterministic and reliable systems that make complex data easier for customers to understand and trust.
• Drive architectural decisions that balance extensibility, performance, maintainability, and operational simplicity.
• Improve observability, testing practices, and production reliability across backend services.
• Partner closely with Product to translate complex business requirements into scalable technical solutions.
• Mentor engineers across different levels and help establish strong backend engineering standards.
• Use AI-powered development tools to increase implementation velocity while maintaining thoughtful technical and product specifications.

What We're Looking For

• Significant experience designing and building complex backend systems in production.
• Strong architectural judgment and the ability to identify risks, propose alternative approaches, and influence technical decisions.
• Expertise in at least one production-grade backend language such as Python, Java, Kotlin, Go, or C#.
• Strong knowledge of relational database design, data modeling, and SQL.
• Experience working with Apache Spark or other ETL/data processing frameworks.
• Experience working with hierarchical, graph-like, or relationship-heavy data structures.
• Familiarity with graph databases or graph-based data modeling is a strong plus.
• Strong written and verbal communication skills.
• Proven experience improving scalability, reliability, observability, and performance in distributed or data-intensive systems.
• Interest in influencing architecture and product direction, rather than simply implementing predefined tickets.
• Ability to collaborate effectively across Engineering, Product, and Analytics in a detail-oriented environment.

Nice to Have

• Experience building SaaS products for mid-market or enterprise customers.
• Experience developing rule-driven systems, validation workflows, approval systems, or governance platforms.
• Experience with AWS and Kubernetes.
• Background in Sales Performance Management, Revenue Operations, Incentive Compensation, or related domains.

Technology Stack Frontend: JavaScript, React, TypeScript Backend: Java, Spring Boot, Django, PostgreSQL Data: Apache Spark, ETL/data processing Infrastructure: AWS, Docker