Senior Solution Engineer - AI & Data for Manufacturing

Snowflake; St. Louis (MO); On-site; USD 165,000 - 217,000; Full time

Job summary

Snowflake is seeking a Senior Solution Engineer to solve complex customer problems, work with the sales team and channel partners, and close large deals. You will demonstrate Snowflake's value across the sales cycle, from initial demonstrations to proofs of concept and implementation.

The role requires deep expertise in data warehousing, cloud technologies, ML/AI, and the ability to articulate business impact to executives.

Qualifications

• 7-8 years of industry experience with a minimum of 5 years within a pre-sales environment.
• Outstanding presenting skills to both technical and executive audiences.
• 5+ years building and deploying machine learning and generative AI solutions in the cloud.
• Broad experience in large-scale DB and/or Data Warehouse tech, ETL, analytics and cloud tech.
• Hands-on expertise with SQL, SQL analytics, and Python.
• Ability to connect customer problems with Snowflake solutions.
• University degree in CS/engineering/math; Masters is a plus.

Responsibilities

• Present Snowflake technology and vision to executives and technical contributors.
• Demonstrate value of Snowflake throughout the sales cycle from demo to POC to design and implementation.
• Stay updated on industry trends and how Snowflake compares to competitors.
• Collaborate with Product, Engineering and Marketing to improve Snowflake's offerings.

Skills

Pre-sales

Executive presenting

SQL

Python

ML/Generative AI

Data warehousing

Cloud technologies

GSIs experience

Education

University degree in computer science, engineering, mathematics, or related fields

Masters in Data Science or Business Administration (a plus)

Job description

Snowflake is seeking a Senior Solution Engineer to solve complex customer problems, work with the sales team and channel partners, and close large deals. You will demonstrate Snowflake's value across the sales cycle, from initial demonstrations to proofs of concept and implementation.

The role requires deep expertise in data warehousing, cloud technologies, ML/AI, and the ability to articulate business impact to executives.