Senior Ps Sales Solutions Architect

Snowflake Snowflake · Data AI · CA-Menlo Park, United States · Professional Services

This role is for a Senior Professional Services Sales Solutions Architect at Snowflake, focusing on selling and delivering professional services engagements related to Snowflake's platform, particularly in the context of the 'agentic enterprise'. The role involves presenting Snowflake technology, acting as a trusted advisor, scoping proposals, collaborating with sales teams, conducting workshops, and demonstrating the value of Snowflake solutions. While the company is focused on the 'agentic enterprise' and mentions AI/ML tools, the core function of this role is sales and professional services delivery, not direct AI/ML model development or research.

What you'd actually do

  1. Present Snowflake technology and vision to executives and technical contributors to customers.
  2. Position yourself as a Trusted Advisor to key customer stakeholders with a focus on achieving their desired Business Outcomes.
  3. Partner with Professional Services Practice Directors and Practice Managers to identify, iterate and scope proposals and Statements of Work, both for packaged services as well as custom Time and Materials projects
  4. Collaborate with Snowflake sales executives and account teams on opportunity development and overall account strategy
  5. Build trust and confidence in Snowflake Professional Services through the delivery of on-site technical/use-case workshops, leadership of video conference meetings, assistance with deep-dive technical issues or questions and public-facing evangelism (LinkedIn, Medium, etc.) of Snowflake

Skills

Required

  • University degree in computer science, engineering, mathematics or related fields, or equivalent experience
  • Minimum 5 years of experience as a solutions architect, data architect, database administrator, or data engineer.
  • Minimum 2 years of practical Snowflake experience, leading or participating in services engagements
  • Minimum 2 years of practical experience with at least one of the three major cloud providers (AWS, Azure or GCP)
  • Understanding of complete data analytics stack and workflow, from ETL to data platform design to BI and analytics tools
  • Hands-on experience in a technical role (SQL, data warehousing, cloud data, analytics, or ML/AI)
  • Either extensive knowledge of and experience with large-scale database technology (e.g. Snowflake, Netezza, Exadata, Teradata, Greenplum, etc.) along with data science/AI/ML use cases and workloads, OR; Experience with AI/ML model development and relevant tools like Sagemaker, DBx, or Azure ML. Additionally candidate must have familiarity with common ML supporting libraries (sklearn, xgboost, pytorch, pandas, etc.)
  • Software development experience with Python, Java , Spark and other Scripting languages
  • Proficiency in implementing data security measures, access controls, and design within the Snowflake platform.
  • Internal and/or external consulting experience.
  • Impeccable communication skills - written, visual and oral. Capable of comfortably engaging audiences from hands-on technologists through C-suite executives.

Nice to have

  • Big 5 Consulting experience
  • Experience selling or supporting the sales process of technical services at the enterprise level
  • Experience with non-relational platforms and tools for large-scale data processing (e.g. Hadoop, HBase)
  • Familiarity and experience with common BI and data exploration tools (e.g. Microstrategy, Looker, Tableau)
  • OLAP Data modeling and data architecture experience
  • Expertise in a core vertical such as Financial Services, Retail, Media & Ente

What the JD emphasized

  • minimum 5 years of experience as a solutions architect, data architect, database administrator, or data engineer
  • minimum 2 years of practical Snowflake experience, leading or participating in services engagements
  • minimum 2 years of practical experience with at least one of the three major cloud providers (AWS, Azure or GCP)
  • Hands-on experience in a technical role (SQL, data warehousing, cloud data, analytics, or ML/AI)
  • Experience with AI/ML model development and relevant tools like Sagemaker, DBx, or Azure ML. Additionally candidate must have familiarity with common ML supporting libraries (sklearn, xgboost, pytorch, pandas, etc.)