Responsibilities
- Serve as a technical expert on Snowflake for AI/ML workloads.
- Design, build, and deploy ML pipelines using Snowflake features and ecosystem partner tools based on customer requirements.
- Build hands-on proofs of concept using SQL, Python, and APIs for generative AI and ML workloads.
- Apply best practices and provide knowledge transfer so customers can extend Snowflake capabilities independently.
- Understand competitive and complementary AI/ML technologies and vendors and position Snowflake accordingly.
- Work with systems integrator consultants to technically position and deploy Snowflake in customer environments.
- Advise customers on resolving technical challenges.
- Help other Services Delivery team members develop their expertise.
- Collaborate with Product Management, Engineering, and Marketing to improve Snowflake products and marketing.
- Travel to customer locations as needed, approximately 25% of the time.
Requirements
- At least 10 years of experience in customer-facing pre-sales or post-sales technical roles.
- Ability to present technical solutions and demonstrations to technical and executive audiences.
- Thorough understanding of the full data science lifecycle, including feature engineering, model development, deployment, and management.
- Strong understanding of MLOps and technologies for deploying and monitoring models.
- Experience with at least one public cloud platform: AWS, Azure, or GCP.
- Experience with at least one data science tool such as SageMaker, Azure ML, Vertex, Dataiku, DataRobot, H2O, or Jupyter Notebooks.
- Experience with large language models, retrieval, and agentic frameworks.
- Hands-on SQL scripting experience and experience with Python, R, Java, or Scala.
- Experience with libraries such as Pandas, PyTorch, TensorFlow, or scikit-learn.
- University degree in computer science, engineering, mathematics, or a related field, or equivalent experience.
- Generative AI, LLM, and vector database experience is a bonus.
- Databricks or Apache Spark experience, including PySpark, is a bonus.
- Experience implementing data pipelines with ETL tools is a bonus.
- Data science experience, enterprise software success, or vertical expertise is a bonus.
Benefits
- Travel to customer sites approximately 25% of the time.
- Salary and benefits information for U.S.-located jobs is provided on the Snowflake Careers Site.
Tech Stack
Categories
About Snowflake
**Snowflake is proud to be the Official Data Collaboration Provider for LA28 and Team USA.** Snowflake delivers the AI Data Cloud — a global network where thousands of organizations mobilize data with near-unlimited scale, concurrency, and performance. Inside the AI Data Cloud, organizations unite their siloed data, easily discover and securely share governed data, and execute diverse analytic workloads. Wherever data or users live, Snowflake delivers a single and seamless experience across multiple public clouds. Snowflake’s platform is the engine that powers and provides access to the AI Data Cloud, creating a solution for data warehousing, data lakes, data engineering, data science, data application development, and data sharing. Join Snowflake customers, partners, and data providers already taking their businesses to new frontiers in the AI Data Cloud.