Sr. Solutions Architect - Strategic AI Native

Databricks Databricks · Data AI · San Francisco, CA · Field Engineering - FE Direct Emerging

Solutions Architect role focused on guiding 'AI native' customers in leveraging the Databricks platform for data engineering, data science, and machine learning workflows. Involves consulting on architectures, implementing proof-of-concepts, and collaborating with sales and product teams. Requires expertise in distributed data systems, Python/SQL, and cloud providers, with a strong preference for data engineering or ML technologies.

What you'd actually do

  1. partner with the sales team and provide technical leadership to help customers understand how Databricks can help solve their business problems.
  2. Consult on Big Data architectures, implement proof of concepts for strategic projects, spanning data engineering, data science and machine learning, and SQL analysis workflows. As well as validating integrations with cloud services, home grown tools, and other 3rd party applications
  3. Collaborate with your fellow Solutions Architects, using your skills to support each other and our users
  4. Become an expert in, promote, and recruit contributors for Databricks inspired open-source projects (Spark, Delta Lake, and MLflow) across the developer community.

Skills

Required

  • 7+ years in a data engineering, data science, technical architecture, or similar pre-sales/consulting role
  • Experience building distributed data systems
  • Comfortable programming in, and debugging, Python and SQL
  • Have built solutions with public cloud providers such as AWS, Azure, or GCP
  • Expertise in one of the following: Data Engineering technologies (Ex: Spark, Hadoop, Kafka) OR Data Science and Machine Learning technologies (Ex: pandas, scikit-learn, pytorch, Tensorflow)
  • Available to travel to customers in your region

Nice to have

  • Databricks Certification
  • Degree in a quantitative discipline (Computer Science, Applied Mathematics, Operations Research)

What the JD emphasized

  • AI native customers
  • data engineering, data science and machine learning

Other signals

  • customer-facing
  • technical leadership
  • architectures and solutions
  • Databricks platform
  • AI native customers