Solutions Architect - Healthcare/life Sciences Team (hls)

Databricks Databricks · Data AI · New York, NY · Field Engineering

Solutions Architect for Databricks' Healthcare/Life Sciences team, focusing on pre-sales and driving adoption of ML & AI within large enterprise accounts. The role involves defining technical strategy, leading customer transformations, and building technical champions, requiring a strong understanding of big data, data science, and cloud technologies, particularly in the HLS space.

What you'd actually do

  1. Working with the Enterprise Account Executive (AE), the Enterprise SA defines and directs the technical strategy for our largest and important accounts, leading to more widespread use of our products and wider and deeper adoption of ML & AI.
  2. You will lean upon your solid background in value selling, technical account management and technical leadership to maximize success in these accounts.
  3. While you work with a team that includes hands-on resources who will build proofs of concept and demonstrate Databricks' products, you need to be technical and must understand the relevance and application of ML & AI within a range of use cases important to the target accounts in the Healthcare & Life Sciences (HLS) space.
  4. You work with multiple clients as the main technical voice for Databricks.
  5. You lead your customers on a transformational journey, helping them to evaluate and adopt Databricks as part of their strategy

Skills

Required

  • pre-sales experience
  • value selling
  • technical account management
  • technical leadership
  • big data
  • data science
  • cloud
  • data-driven business transformation
  • Python
  • SQL
  • Scala

Nice to have

  • experience working very large (> $1m ARR), global accounts
  • relationships with executives and influencers
  • convincing point-of-view to important decision-makers
  • structured mentorship for other team members

What the JD emphasized

  • must understand the relevance and application of ML & AI

Other signals

  • driving adoption of ML & AI
  • value selling
  • technical account management
  • technical leadership
  • ML & AI within a range of use cases