Where Data Does More. Join the Snowflake team.
We are looking for people who have a strong background in data science and cloud architecture to join our Professional Services team to help create exciting new offerings and capabilities for our customers! This team will be working with customers using Snowflake to expand their use of the Snowflake Data Cloud to bring data science pipelines from ideation to deployment, and beyond using Snowflake's features and its extensive partner ecosystem. The role will be more strategic, advising our clients on best practices and advice to implement Data Science workloads on Snowflake. You will be designing solutions based on requirements and coordinating with customer teams, and where needed Systems Integrators, while maintaining oversight and direction to ensure successful outcomes
AS A SOLUTIONS ARCHITECT - AI/ML AT SNOWFLAKE, YOU WILL:Be a technical expert on all aspects of Snowflake in relation to the AI/ML workload.
Provide customers with best practices and advise as it relates to Data Science workloads on Snowflake
Build, deploy and ML pipelines using Snowflake features and/or Snowflake ecosystem partner tools based on customer requirements.
Work hands-on where needed using SQL, Python, Java and/or Scala to build POCs that demonstrate implementation techniques and best practices on Snowflake technology within the Data Science workload.
Follow best practices, including ensuring knowledge transfer so that customers are properly enabled and are able to extend the capabilities of Snowflake on their own
Maintain deep understanding of competitive and complementary technologies and vendors within the AI/ML space, and how to position Snowflake in relation to them
Work with System Integrator consultants at a deep technical level to successfully position and deploy Snowflake in customer environments
Provide guidance on how to resolve customer-specific technical challenges.
Support other members of the Professional Services team develop their expertise.
Collaborate with Product Management, Engineering, and Marketing to continuously improve Snowflake’s products and marketing.
Minimum 5 years experience working with customers in a pre-sales or post-sales technical role.
Outstanding skills presenting to both technical and executive audiences, whether impromptu on a whiteboard or using presentations and demos
Thorough understanding of the complete Data Science life-cycle including feature engineering, model development, model deployment and model management.
Strong understanding of MLOps, coupled with technologies and methodologies for deploying and monitoring models.
Experience and understanding of at least one public cloud platform (AWS, Azure or GCP)
Experience with at least one Data Science tool such as AWS Sagemaker, AzureML, Dataiku, Datarobot, H2O, and Jupyter Notebooks,
Hands-on scripting experience with SQL and at least one of the following; Python, Java or Scala.
Experience with libraries such as Pandas, PyTorch, TensorFlow, SciKit-Learn or similar.
University degree in data science, computer science, engineering, mathematics or related fields, or equivalent experience
Experience with GenerativeAI, LLMs and Vector Databases,
Experience with Databricks/Apache Spark
Experience implementing data pipelines using ETL tools
Experience working in a Data Science role
Proven success at enterprise software
Vertical expertise in a core vertical such as FSI, Retail, Manufacturing etc.
Every Snowflake employee is expected to follow the company’s confidentiality and security standards for handling sensitive data. Snowflake employees must abide by the company’s data security plan as an essential part of their duties. It is every employee's duty to keep customer information secure and confidential.
Snowflake is growing fast, and we’re scaling our team to help enable and accelerate our growth. We are looking for people who share our values, challenge ordinary thinking, and push the pace of innovation while building a future for themselves and Snowflake.
How do you want to make your impact?
For jobs located in the United States, please visit the job posting on the Snowflake Careers Site for salary and benefits information: careers.snowflake.com
Snowflake Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Snowflake and has not been reviewed or approved by Snowflake.
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Equity Value & Accessibility — Equity grants (RSUs) and an ESPP are central to total compensation and are described as highly valuable. Feedback suggests many see equity as a major satisfaction driver with meaningful upside potential.
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Fair & Transparent Compensation — Pay is considered competitive and accompanied by clear communication on salary, equity, and advancement. Feedback suggests pay practices emphasize fairness and transparency.
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Parental & Family Support — Paid parental leave, fertility benefits, adoption assistance, and family planning resources are notably comprehensive. Feedback suggests these programs materially support major life events.
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What We Do
Snowflake powers the end-to-end data lifecycle – from ingesting and processing data to analyzing and modeling it, to building and sharing data and AI applications – helping engineers, analysts, and leaders innovate faster and achieve more with their data. We're on a mission to empower every enterprise to achieve its full potential through data and AI.
Why Work With Us
Snowflake is where data does more, and so do you. More innovating, more growing, and more collaborating. Here, you’ll find the sweet spot between building big and moving fast, in technology and your career.
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