Solution Engineer - Data Cloud Architect - Apps

Snowflake Snowflake · Data AI · New York, NY · Remote · Solution Engineering

This role focuses on enabling partners to build and deploy AI-native applications and ML models on the Snowflake Data Cloud. The Solution Engineer will provide technical expertise, training, and architectural guidance to partners, helping them leverage Snowflake's platform for SaaS native app development, data optimization, and Gen AI solutions. Key responsibilities include running training sessions, developing technical strategies, and assisting partners with deploying ML models and building Gen AI applications within Snowflake.

What you'd actually do

  1. Run training sessions, workshops, webinars to help Partners become proficient in Snowflake.
  2. Help Solution Providers/Practice Leads with technical strategies that enable them to sell their offerings on Snowflake.
  3. Keep Partners up to date on key Snowflake product updates and future roadmaps to help them represent Snowflake to their clients about latest technology solutions and benefits.
  4. Run technical enablement programs to provide best practices and solution design workshops to help Partners create effective solutions.
  5. Work with large-scale datasets, preprocess them, and create appropriate data representations

Skills

Required

  • Excellent verbal and written communication skills in English
  • Technical expertise
  • Deep technical expertise
  • Proven track record of successfully working with large partners
  • Strong experience with databases like SQL Server / Oracle/ My SQL/ NoSQL DBs
  • Strong experience with data warehouses like Azure Synapse / Redshift / Big Query
  • In-depth knowledge and hands-on experience in Data Engineering, Spark, Big Data
  • Experience and strong knowledge on Docker and how to dockerize Python based applications
  • Working knowledge on API’s and how to build and expose applications as APIs
  • Proficiency in Agile development practices and Continuous Integration/Continuous Deployment (CI/CD), including DataOps and MLops
  • Familiarity with cloud platforms (e.g., Azure, AWS) and distributed computing
  • Excellent problem-solving skills
  • Experience using Big Data or Cloud integration technologies such as Azure Data Factory, AWS Glue, AWS Lambda, etc.
  • High level overview and knowledgeable on ML development and Generative AI. How to deploy ML models to productions.

Nice to have

  • Knowledge on Container networking and overview on Kubernetes
  • Ability to work independently and collaboratively

What the JD emphasized

  • deep technical expertise
  • proven track record of successfully working with large partners
  • Building Gen AI-based applications
  • deploying ML models in Snowflake

Other signals

  • AI-native thinkers
  • AI as a high-trust collaborator
  • experimental mindset
  • Building Gen AI-based applications
  • deploying ML models in Snowflake