What are the responsibilities and job description for the Enterprise Sales Engineer (Remote) position at Cube Dev?
At Cube, we are building a technology stack for modern analytics. If you are fascinated by the software that powers large technology companies but want the challenges and freedom that come with working in a small startup, then the job at Cube is for you. We are a small and dedicated team in San Francisco, funded by top-tier SV investors, working on making advanced analytics infrastructure developed at large tech companies accessible to all developers around the world.We're seeking an experienced Enterprise Sales Engineer to serve as a strategic technical partner for our enterprise customers, helping them navigate complex data challenges through Cube's semantic layer. This role offers the opportunity to influence how modern data teams adopt Cube by collaborating with Account Executives, leading solution design and evaluations, contributing to the product roadmap, and engaging prospects through tailored demos, pilots, and thought leadership.What You'll Do
- Become a confident subject-matter expert on semantic layers, data modeling, performance tuning, and modern data stacks
- Partner with Account Executives to deliver tailored demos, technical deep dives
- Own and document the technical relationship with customers: requirements gathering, solution architecture, integrations, and success criteria for pilots or POCs
- Translate complex data problems into elegant solutions using our semantic layer and integrations with BI tools, data warehouses, and governance systems.
- Document and refine relevant customer feedback for product feature and partner integration roadmap
- Collaborate with account executives on RFP/RFI responses
- Lead security and architecture reviews with enterprise prospects
- Generate pipeline by writing blogs and delivering webinars
- 5 years of experience in Sales Engineering, Solutions Consulting, or Customer Success roles
- Previous experience supporting enterprise SaaS sales, ideally with complex technical products (data platforms, analytics tools, or semantic layers)
- Deep understanding of enterprise data cloud environments and the modern data stack: cloud data warehouses, data transformation, and BI tools
- Strong SQL skills and experience with data modeling concepts
- Excellent communication skills to clearly articulate value to both technical and non-technical audiences
- Comfortable working at a startup, problem-solving on the fly, and working cross-functionally
- Experience working with modern semantic layers (e.g., Cube, LookML, MetricFlow, etc.)
- Experience working with legacy OLAP semantics (e.g. Microsoft, Oracle, SAP, etc.)
- Expert in at least one of the high-level languages such as Node.js, Ruby, Python, Java, Scala, C#, or similar
