Expert-level SQL proficiency with complex query writing and performance optimization.
Strong data analysis skills for exploring data and communicating insights.
Programming experience in JavaScript or Python, with API and data transformation capabilities.
3+ years in solutions architecture, data engineering, or a similar technical customer-facing role.
Deep understanding of the modern data stack, including data warehouses and BI platforms.
Experience with semantic layers or BI modeling frameworks like LookML or dbt metrics.
Strong communication skills to convey technical concepts to diverse audiences.
Responsibilities
Design and architect end-to-end semantic layer solutions integrating with customer data warehouses.
Build comprehensive data models in YAML or JavaScript defining metrics and business logic.
Develop proof-of-concepts and lead technical discovery sessions to assess customer data architecture.
Guide customers on best practices for data modeling and performance optimization.
Run hands-on workshops and training sessions for customer teams.
Write complex SQL to analyze customer data and validate solution designs.
Serve as a trusted technical advisor throughout the customer lifecycle, providing feedback to Product and Engineering.
Benefits
Fully remote work environment with flexibility to work from anywhere.
Opportunity to collaborate with a highly skilled and supportive team.
Engagement in hands-on workshops and training, enhancing both personal and professional growth.
Involvement in shaping product development through customer feedback.
Occasional travel opportunities to customer sites and company events.
Full Job Description
Solutions Architect
As a Solutions Architect at Cube, you'll be the technical bridge between our product and our 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 have a direct impact on customer success.
What you will do:
Design and architect end-to-end semantic layer solutions using Cube, integrating with customers' existing data warehouses (Snowflake, BigQuery, Redshift).
Build comprehensive data models in YAML or JavaScript that define metrics, dimensions, and business logic.
Develop proof-of-concepts and technical demonstrations on customer data, and lead technical discovery sessions to understand data architecture and requirements.
Guide customers on best practices for data modeling, caching strategies, access control, and performance optimization.
Run hands-on workshops and training to enable customer teams, and partner with Sales to provide technical expertise during the evaluation process.
Write complex SQL to analyze customer data and validate solution designs, and build integrations between Cube and downstream BI tools, notebooks, and custom applications.
Serve as a trusted technical advisor across the customer lifecycle, and bring customer feedback back to Product and Engineering to influence the roadmap.
Who you are:
Expert-level SQL proficiency: you can write complex queries, optimize performance, and understand query execution plans.
Strong data analysis skills: you explore data, identify patterns, validate metrics, and communicate insights.
Programming experience in JavaScript or Python, comfortable working with APIs and building data transformations.
3+ years in solutions architecture, data engineering, analytics engineering, or a similar technical customer-facing role.
Deep understanding of the modern data stack: data warehouses, transformation tools, and BI platforms.
Experience with semantic or metrics layers, or BI modeling frameworks (LookML, dbt metrics, or similar).
Strong communication skills: you can translate technical concepts for both technical and business audiences.
Bonus points:
Prior experience with Cube.js or similar semantic layer platforms.
Background in analytics engineering or data platform roles, and familiarity with dimensional modeling best practices.
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) and an understanding of multi-tenancy, access control, and data governance.
Experience with embedded analytics or building data-powered applications.
Familiarity with AI/LLM integration with semantic layers, and contributions to open-source data projects.
This role is customer-facing and involves occasional travel to customer sites and company events.
We're a fully remote company based in San Francisco. You can work from anywhere and join our highly collaborative team.
About Cube Dev
Cube Dev is a software development company that specializes in creating custom software solutions for businesses. They have a team of experienced developers who work closely with clients to understand their needs and create software that meets those needs. Cube Dev has a reputation for delivering high-quality software on time and within budget. They have worked with a variety of clients across different industries, including healthcare, finance, and retail. Cube Dev is committed to staying up-to-date with the latest technologies and trends in software development to ensure that they are always providing the best possible solutions to their clients.
