At Cube, we're redefining how organizations deliver, consume, and automate data and analytics across teams, tools, and AI agents.Our mission is to enable Agentic Analytics — where AI agents work alongside humans on a shared semantic foundation With 19,000\+ GitHub stars and 13,000\+ community members, Cube is trusted by companies like SecurityScorecard, Webflow, The Linux Foundation, Cloud Academy, and SamCart.Our platform empowers AI agents with a universal semantic foundation — enabling autonomous analytics at scale while maintaining the same consistency, security, and performance across BI tools, spreadsheets, and embedded applications. **As a Solutions Architect at Cube**, you'll be the technical bridge between our product and customers' data infrastructure. You'll work hands\-on with prospects and customers across industries to design, implement, and optimize semantic layer architectures that solve complex data challenges. This is a highly technical, customer\-facing role where your SQL expertise and data analysis skills will have a direct impact on customer success. **What you will do** **Technical Leadership \& Architecture** * Design and architect end\-to\-end semantic layer solutions using Cube, integrating with customers' existing data warehouses (e.g., Snowflake, BigQuery, Redshift). * Build comprehensive data models in YAML or JavaScript that define metrics, dimensions, and business logic to support data analysis and decision\-making. * Develop proof\-of\-concepts and technical demonstrations that showcase Cube's capabilities on customer data. * Guide customers on best practices for data modeling, caching strategies, access control, and performance optimization. **Customer Engagement** * Lead technical discovery sessions to understand customer data architecture, analytics requirements, and business objectives. * Conduct hands\-on workshops and training sessions to enable customer teams to use Cube effectively. * Partner with Sales to provide technical expertise during the evaluation process. * Serve as a trusted technical advisor throughout the customer lifecycle, from pre\-sales through post\-implementation. **Solution Development** * Write complex SQL queries to analyze customer data and validate solution designs. * Conduct data analysis to identify opportunities for optimization and architectural * improvements. * Build integrations between Cube and downstream tools (BI platforms, notebooks, * custom applications). * Create technical documentation, reference architectures, and implementation guides. **Product Collaboration** * Provide customer feedback to Product and Engineering teams to influence the roadmap. * Contribute to internal tooling and automation to improve solution delivery. * Develop reusable patterns and frameworks for common implementation scenarios to facilitate efficient and consistent development. **Who you are** * Expert\-level SQL proficiency \- You can write complex queries, optimize performance, and understand query execution plans. This is the foundational skill for success in this Role. * Strong data analysis capabilities \- You understand how to explore data, identify patterns, validate metrics, and communicate insights. * Programming experience in JavaScript OR Python \- You're comfortable reading and writing code, working with APIs, and building data transformations. * 3\+ years in solutions architecture, data engineering, analytics engineering, or similar technical customer\-facing roles. * Deep understanding of modern data stack architecture (data warehouses, transformation tools, BI platforms). * Experience with semantic layers, metrics layers, or BI modeling frameworks (LookML, dbt metrics, etc.). * Strong communication skills \- you can translate technical concepts for both technical and business audiences. **Highly Valued** * Prior experience with Cube.js or similar semantic layer platforms. * Background in analytics engineering or data platform roles. * Experience with data modeling best practices and dimensional modeling. * Familiarity with REST/GraphQL APIs and how applications consume analytics. * Knowledge of caching strategies and performance optimization for analytics workloads. * Experience with cloud data warehouses (Snowflake, BigQuery, Databricks, Redshift). * Understanding of multi\-tenancy, access control, and data governance requirements. **Nice to Have** * Experience with embedded analytics or building data\-powered applications. * Knowledge of both JavaScript AND Python ecosystems. * Contributions to open\-source data projects. * Familiarity with AI/LLM integration with semantic layers. **What Success Looks Like** * Customers successfully deploy Cube into production with well\-architected, performant Solutions. * High satisfaction scores from customers with technical guidance and support. * Ability to handle complex, multi\-source data modeling scenarios. * Proactive identification of opportunities to expand Cube usage within customer Organizations. * Contributions to the internal knowledge base and solution patterns that benefit the entire Team. **Why Join Cube** * Work with cutting\-edge semantic layer technology at the intersection of data engineering, analytics, and AI. * Collaborate with a passionate team that includes the creators of the open\-source Cube Project. * Make a direct impact on how thousands of companies organize and access their data. * Competitive compensation. * Remote\-friendly culture with flexible work arrangements.