Solutions Architect - Digital Native Business

Databricks Databricks · Data AI · San Francisco, CA · Field Engineering

Solutions Architect for Databricks' Digital Natives team, focusing on big data, data engineering, data science, and machine learning solutions. The role involves collaborating with customers and internal teams to design architectures, implement proof-of-concepts, and provide technical leadership using the Databricks platform and APIs. Expertise in either Data Engineering or Data Science/ML technologies is required.

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

  • Python
  • SQL
  • Data Engineering technologies (Spark, Hadoop, Kafka)
  • Data Science and Machine Learning technologies (pandas, scikit-learn, pytorch, Tensorflow)
  • Public cloud providers (AWS, Azure, GCP)
  • Distributed data systems
  • Technical architecture
  • Pre-sales/consulting

Nice to have

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

What the JD emphasized

  • 5+ 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 OR Data Science and Machine Learning technologies