Senior Solution Engineer, Healthcare & Life Science

Snowflake Snowflake · Data AI · NC, United States · Remote · Solution Engineering

This role is for a Senior Solution Engineer in the Healthcare & Life Science domain at Snowflake. The primary focus is on working with sales teams and partners to understand customer needs, provide compelling demonstrations, support proofs of concept, and close deals. While the role requires experience in building and deploying ML/GenAI solutions, its core function is pre-sales and customer-facing technical support, not direct AI model development or deployment as a primary deliverable.

What you'd actually do

  1. Present Snowflake technology and vision to executives and technical contributors at prospects and customers
  2. Work hands-on with prospects and customers to demonstrate and communicate the value of Snowflake technology throughout the sales cycle, from demo to proof of concept to design and implementation
  3. Immerse yourself in the ever-evolving industry, maintaining a deep understanding of competitive and complementary technologies and vendors and how to position Snowflake in relation to them.
  4. Collaborate with Product Management, Engineering, and Marketing to continuously improve Snowflake’s products and marketing

Skills

Required

  • 7-8 years of industry experience
  • 5+ years within a pre-sales environment
  • Outstanding presenting skills to both technical and executive audiences
  • 5+ years of experience building and deploying machine learning and generative AI solutions in the cloud
  • Broad range of experience within large-scale Database and/or Data Warehouse technology, ETL, analytics and cloud technologies
  • Hands-on expertise with SQL, SQL analytics, and Python
  • Ability to connect a customer’s specific business problems and Snowflake’s solutions
  • Ability to do deep discovery of customer’s architecture framework and connect those with Snowflake Data Architecture

Nice to have

  • Masters in DataScience or Business Administration
  • Experience with GSIs (EY, Deloitte, Accenture, etc)

What the JD emphasized

  • 5+ years of experience building and deploying machine learning and generative AI solutions in the cloud