Solutions Architect - Digital Native Business, Strategic

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

Solutions Architect for Databricks' Digital Natives team, focusing on data engineering, data science, and ML. The role involves collaborating with strategic customers and internal teams to design and implement solutions using the Databricks platform, guiding customers through competitive landscapes and best practices, and driving technical discovery to accelerate time-to-value. The role emphasizes building distributed data systems, programming in Python and SQL, and expertise with public cloud providers.

What you'd actually do

  1. You will partner with the sales team and provide technical leadership to help customers understand how Databricks can help solve their business problems.
  2. Drive technical discovery and solution design, focusing on winning competitive deals and accelerating time-to-value in strategic accounts.
  3. Continuously research & learn new technologies and their implementations on Databricks
  4. 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
  5. 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

  • 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
  • Built solutions with public cloud providers such as AWS, Azure, or GCP
  • Strong executive presence
  • Ability to influence C/VP-level stakeholders
  • Align technical solutions to strategic business priorities
  • 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

  • production scale
  • deep technical aptitude
  • deep sense of ownership
  • deeply curious
  • operating with confidence in ambiguous situations
  • extremely adaptable
  • technical leadership
  • winning competitive deals
  • accelerating time-to-value
  • strategic accounts
  • research & learn new technologies
  • Big Data architectures
  • strategic projects
  • data engineering
  • data science
  • machine learning
  • SQL analysis workflows
  • cloud services
  • home grown tools
  • 3rd party applications
  • open-source projects
  • developer community
  • account penetration strategies
  • winning technical decision-makers
  • building new customer champions
  • trusted advisor relationships
  • senior and executive stakeholders
  • business value
  • outcomes-driven terms
  • 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
  • built solutions with public cloud providers such as AWS, Azure, or GCP
  • Expertise in one of the following
  • Strong executive presence
  • influence C/VP-level stakeholders
  • align technical solutions to strategic business priorities
  • Available to travel to customers in your region
  • Degree in a quantitative discipline (Computer Science, Applied Mathematics, Operations Research)

Other signals

  • customer-facing
  • technical leadership
  • production scale
  • architectures and solutions