Staff Application Architect

Role overview

Key responsibilities

• Design and maintain a low-latency analytics stack from ingestion through the semantic layer and embedded analytics UI.
• Build scalable Ruby on Rails backend services and APIs.
• Build ingestion pipelines from PostgreSQL and Kafka or Kinesis into an OLAP data store.
• Develop Cube.js models for complex sales metrics and maintain consistency across product surfaces.
• Integrate and customize embedded BI platforms through SDKs and APIs, including authentication, theming, and customization.
• Optimize query performance, pre-aggregations, API response times, and dashboard load times.
• Design REST and GraphQL data models for embedded analytics and third-party consumers.
• Implement multi-tenant security and row-level data isolation.
• Set technical direction, mentor engineers, and drive cross-team architectural decisions.

Technical requirements

• Strong backend experience with Ruby on Rails and embedded analytics or BI integration in a SaaS product.
• Strong PostgreSQL knowledge, including analytical query optimization.
• Experience with Cube.js or a comparable semantic layer, pre-aggregations, and multi-tenant security contexts.
• Hands-on experience with Kafka or similar event-streaming systems.
• Mastery of complex SQL and code-based data schemas.
• A track record of leading cross-team initiatives, mentoring engineers, and making production-scale architectural tradeoffs.

Bonus qualifications

• Direct experience embedding ThoughtSpot through its Embed SDK, Liveboards, or TML and metadata APIs.
• Experience building analytics for CRM or sales technology ecosystems.
• Experience with OLAP or columnar stores such as Apache Pinot, ClickHouse, or StarRocks.
• Experience with dbt, Airflow, or Spark for transformation and orchestration.
• Experience with Terraform or Kubernetes for services and data clusters.
• Proficiency using AI tools to navigate legacy codebases and close technical gaps.

Technology scope

• Ruby on Rails, PostgreSQL, Kafka or Kinesis, Cube.js, complex SQL, REST, GraphQL, and embedded analytics platforms.
• Possible embedded analytics platforms include ThoughtSpot, Looker, Sigma, and embedded Power BI.