Cube

• Driving projects from idea to release, including scoping, technical design, implementation, and deployment. • Writing and reviewing technical specs for features that span multiple applications to ensure performance and scalability. • Contributing to our AI-assisted development environment by building skills and coordinating agents. • Solving high-complexity problems like performance bottlenecks and intricate state management challenges. • Implementing and managing observability strategies using tools like Datadog to proactively monitor and improve customer experiences and application health. • Mentoring the team through pair programming and pragmatic code reviews. • Partnering with Product and Design to ensure technical decisions align with customer needs and business goals.

• Customer outreach and engagement • Managing relationships with prospective clients • Leading product demonstrations • Negotiating contracts • Meeting sales quotas • Identifying customer needs and providing solutions that deliver value • Collaborating with cross-functional teams to ensure client satisfaction and success

• Drive to hit a quarterly goal of qualified meetings from our variety of inbound leads sources: paid and organic channels, free signup (PLG) and Open Source users. • Develop Outbound campaigns that drive interest, user signups and qualified meetings for sales. • Continually optimize target audience, sales cadences, and pitches for optimal results. • Optimize outreach through a combination of traditional and new channels and message development: email, phone, LinkedIn, AI and investigate and try new methods. • Improve GDR efficiency through the implementation of new tools. • Work collaboratively with Product, Sales, Customer Success, and Operations to continuously and creatively improve conversion of top-of-funnel interest to sales funnel. • Provide consistent visibility and insights into sales development activities, hand-off, dispositions, KPI and outcomes by region, team, and individual. • Maintain and improve the data quality of leads and contacts in the CRM, including sales opportunity detail, contact and account data, and call/meeting history. • Constantly seek new target audiences for outreach and conversion into the sales funnel, while converting existing leads like free signups, OSS users, and other inbound interest.

• Cube is hiring a Senior Backend Engineer to join our Engineering team. • You’ll partner closely with Engineering, Product, Marketing, and Customer Success, and you’ll report to one of our Engineering Managers. • This role carries meaningful ownership and influence across the team and the product. • Our mission is to create an extremely simple and intuitive product in an industry—Financial Planning & Analysis (FP&A)—that is inherently complex. • We’re looking for a senior engineer who thrives in the middle of complex systems—not just greenfield projects—and who takes pride in evolving large, long-lived codebases under real business constraints.

• Review, analyze, and collaborate with developers, product managers, and stakeholders to clarify feature requirements and acceptance criteria • Design and execute comprehensive test strategies including functional, regression, smoke, and exploratory testing • Identify and document defects with clear replication steps during testing • Verify bug fixes and perform retesting • Triage and translate customer issues into actionable reproduction steps for engineering • Participate in Agile ceremonies

• Design and architect end-to-end semantic layer solutions using Cube • Build comprehensive data models in YAML or JavaScript • Develop proof-of-concepts and technical demonstrations • Lead technical discovery sessions with customers • Write complex SQL queries to analyze customer data • Provide customer feedback to Product and Engineering teams

• Designing and maintaining cloud-native infrastructure for a globally distributed analytics platform • Building internal platform tooling to improve developer velocity, observability, and deployment safety • Scaling multi-tenant systems that serve large volumes of analytical queries with strict latency requirements • Improving reliability, fault tolerance, and disaster recovery for Cube cloud platform • Operating Kubernetes-based environments and evolving our deployment and release pipelines • Implementing monitoring, alerting, and incident response practices for a high-availability system

• Building and evolving the Cube Cloud platform web application and developer-facing interfaces • Designing and implementing backend APIs that power configuration, management, and analytics workflows • Translating complex analytics concepts into clear and usable UI/UX • Improving performance, reliability, and scalability of end-user features • Working with large datasets and real-time analytics results in frontend applications • Collaborating with Core engineers to integrate new Cube capabilities into the product