Lead Specialist Solutions Architect - Built Partners

At Databricks, our core principles are at the heart of everything we do; creating a culture of proactiveness and a customer‑centric mindset guides us to create a unified platform that makes data science and analytics accessible to everyone. We aim to inspire our customers to make informed decisions that push their business forward. We provide a user‑friendly and intuitive platform that makes it easy to turn insights into action and fosters a culture of creativity, experimentation, and continuous improvement.

You will be an essential part of this mission, using your technical expertise to demonstrate how our Data Intelligence Platform can help customers solve their complex data challenges. You'll work with a collaborative, customer‑focused team that values innovation and creativity, using your skills to create customized solutions to help our customers achieve their goals and guide their businesses forward. Join us in our quest to change how people work with data and make a better world!

As a Field Engineer specializing in Databricks Strategic Built‑on Partners, you will be the technical expert supporting strategic partners who build their B2B, customer‑facing products on the Databricks platform. You will play a central role in solution architecture, enablement, evaluation, and collaborative innovation, helping partners design, deploy, and optimize robust and scalable data and AI‑powered solutions, powered by Databricks.

• Partner Technical Leadership:
  Serve as the technical authority for prospective and current Built‑on strategic partners building products and solutions on Databricks.
• Well‑Architected Framework:
  Develop and continuously optimize a framework of best practices and guidelines for building and operating reliable, secure, efficient, and cost‑effective workloads on Databricks.
• Solution Architecture:
  Guide partners through solution design and integration, delivering architecture best practices for data engineering, data science, and AI workloads.
• Enablement & Workshops:
  Deliver technical enablement, training, and workshops to upskill partner technical teams on Databricks’ capabilities and advanced features.
• Proof of Concept Execution:
  Lead and support POCs and pilots, addressing technical challenges and highlighting the value of Databricks in the Built‑on partner solution context.
• Technical Escalation Management:
  Provide direct technical support as an escalation point for deployment, integration, and performance issues.
• Relationship Management:
  Build strong, trust‑based relationships with partner engineering teams and collaborate closely with Databricks’ internal Product, Field Engineering, and Sales teams.
• Thought Leadership:
  Represent Databricks in strategic partner meetings and events. Advocate for the needs of Built‑on partners internally to influence the Databricks product roadmap.
• Best Practice Development:
  Develop and share reusable frameworks, guides, and reference architectures for partner enablement.
• Continuous Learning:
  Stay up‑to‑date with new data and AI trends, platform features, and industry best practices to ensure partners benefit from cutting‑edge capabilities.

• Minimum 7 years’ experience in field engineering, solution architecture, or partner‑facing technical roles in the cloud, data, or AI/ML domains.
• Deep hands‑on expertise with Databricks, Spark, and related data/AI platforms.
• Proven capability in designing and delivering large‑scale data and AI architectures for partners or enterprise customers.
• Strong proficiency in cloud‑native architectures (Azure, AWS, GCP), Python and/or Scala, and orchestration frameworks.
• Demonstrated experience managing technical relationships and projects in a partner ecosystem.
• Excellent communication, presentation, and consultative skills.
• Experience conducting technical workshops and enablement sessions.
• Ability to lead and resolve complex technical challenges in fast‑paced, ambiguous environments.

• Experience with building or supporting ISV solutions, SaaS platforms, or integration ecosystems.
• Working knowledge of ML/AI frameworks, data governance, security, and…