Sr. Staff Partner Engineer

Databricks Databricks · Data AI · San Francisco, CA · Product

This role is for a Sr. Staff Partner Engineer at Databricks, focusing on evolving the technical foundation of the Built-On program. The role involves owning the Partner Well-Architected Framework, creating reference implementations, and collaborating with strategic partners to co-architect their platforms. It also involves shaping the platform roadmap based on ecosystem insights and partner requirements. While the company is an AI company and the role mentions AI/ML domains and AI-assisted tools, the core responsibilities are focused on architecture, engineering, and partner enablement within the Databricks ecosystem, not directly building or shipping AI models or core AI infrastructure.

What you'd actually do

  1. Own the design, governance, and evolution of the Partner Well-Architected Framework, defining core architecture standards and validation mechanisms for Built-On solutions.
  2. Work with director, VP, and CPO-level partner architects to design, review, and validate their platforms for security, scalability, and alignment with Databricks standards.
  3. Build and maintain production-grade reference implementations, blueprints, and technical examples that demonstrate end-to-end Built-On architectures in practice.
  4. Drive alignment across Product, Engineering, and Field teams to shape platform roadmap priorities based on ecosystem insights and partner requirements.
  5. Evangelize the framework through clear technical documentation and published guidance, validating partner solutions and approving architectures for Built-On program inclusion.

Skills

Required

  • Solution architecture
  • Field engineering
  • Cloud, data, or AI/ML domains
  • Distributed SaaS platform architectures
  • Multi-tenant SaaS architectures
  • Authentication patterns (OAuth 2.0, OIDC, SSO federation)
  • Data isolation
  • Security best practices
  • Hands-on software development
  • Production-grade applications
  • CI/CD
  • DevOps practices
  • Architectural quality enforcement
  • Databricks product suite
  • Cloud-native architectures (AWS, Azure, GCP)
  • Managing senior technical relationships (VP/C-level)
  • Complex projects in partner ecosystems
  • Communication skills
  • Consultative skills

Nice to have

  • Building B2B applications on Databricks
  • Hyperscaler Well-Architected Frameworks
  • Modern development workflows
  • AI-assisted development tools (Cursor, GitHub Copilot, Claude)
  • Consulting or services industry background
  • Mentoring senior technical talent
  • Leading cross-functional initiatives

What the JD emphasized

  • 10+ years of experience in solution architecture, field engineering, or technical roles in cloud, data, or AI/ML domains, with proven experience designing and owning distributed SaaS platform architectures from end to end.
  • Deep expertise in multi-tenant SaaS architectures including authentication patterns (OAuth 2.0, OIDC, SSO federation), data isolation, and security best practices.
  • Strong hands-on software development experience with ability to build production-grade applications, combined with expertise in CI/CD, DevOps practices, and architectural quality enforcement.
  • Technical expert on Databricks product suite and cloud-native architectures (AWS, Azure, GCP), with ability to translate partner requirements into platform priorities.
  • Demonstrated experience managing senior technical relationships (VP/C-level) and complex projects in partner ecosystems, with excellent communication and consultative skills.