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Snowflake Presales Architect (Data & AI)

Jade GlobalSan Jose, CA🇺🇸United StatesPosted 15 Aug 2026

Why This Role Stands Out

This hybrid role offers an exceptional opportunity to drive cutting-edge Data & AI presales solutions, shaping innovative strategies and building impactful solutions with Snowflake. You'll thrive here if you possess deep technical expertise in modern data platforms and AI, coupled with a passion for client engagement and solution design. Don't miss this chance to advance your career at Jade Global!

Quick Overview

Work Type
Hybrid
Level
Mid Senior

Job Description

Snowflake Presales Architect (Data & AI)1Role Overview

We are looking for a highly skilled Snowflake Presales Architect with strong expertise in modern data platforms and emerging AI capabilities. This role will drive end-to-end presales for Data & AI opportunities, combining deep Snowflake knowledge with the ability to position AI/ML-driven use cases for enterprise customers.

The role demands a balance of technical depth, presales leadership, and innovation mindset, with ~50% billability on strategic engagements.
Key Responsibilities
  • Lead presales solutioning for Data, Analytics, and AI-driven opportunities with Snowflake at the core
  • Partner with sales to shape deals and position data + AI solutions aligned to business outcomes
  • Design scalable architectures leveraging Snowflake + AI/ML ecosystem (Snowpark, Cortex, external ML platforms)
  • Conduct discovery workshops to identify opportunities for AI/GenAI use cases (e.g., predictive analytics, NLP, automation)
  • Build POCs and demos showcasing AI-infused data platforms
  • Define data + AI architecture patterns, including data pipelines, feature engineering, and model integration
  • Provide solution estimates, sizing, and cost optimization strategies
  • Act as a solution anchor on delivery (~50% billable) for key programs
  • Collaborate with partners (Snowflake, cloud, AI ecosystem) to drive joint GTM initiatives
  • Contribute to AI accelerators, reusable frameworks, and thought leadership
Required Skills & Qualifications
  • 12+ years in Data Engineering / Data Architecture / Analytics
  • 4+ years of strong hands-on experience with Snowflake implementations and architecture
  • Solid understanding of:
    • Data warehousing, lakehouse, and modern data stack
    • ETL/ELT tools (dbt, Informatica, etc.)
    • SQL, performance tuning, and data modeling
  • Experience with at least one cloud: AWS / Azure / Google Cloud Platform
  • Proven experience in presales / solution consulting roles
  • Strong understanding of how data platforms enable AI/ML use cases
AI-Specific Expectations
  • Working knowledge of AI/ML concepts (feature engineering, model lifecycle, inference patterns)
  • Exposure to Snowflake AI capabilities (Snowpark, Cortex) or similar ecosystems
  • Familiarity with GenAI use cases (LLMs, embeddings, retrieval-augmented generation - RAG)
  • Ability to position business-driven AI use cases (customer analytics, personalization, risk/fraud, automation)
  • Experience integrating data platforms with ML frameworks (e.g., Python-based ecosystems, external AI platforms)
  • Understanding of data governance, privacy, and ethical AI considerations
Preferred Qualifications
  • Experience with tools like Databricks, MLflow, Power BI, Tableau
  • Exposure to MLOps / LLMOps concepts
  • Snowflake certifications preferred
  • Experience contributing to AI/data GTM strategies or industry solutions
Key Competencies
  • Strong client engagement and storytelling skills (Data + AI narrative)
  • Ability to translate business problems into data + AI solutions
  • Strategic mindset with sales orientation
  • Strong collaboration across sales, delivery, and alliances
  • Ability to operate in a fast-paced, innovation-driven environment
Success Metrics
  • Contribution to deal wins and AI-led opportunities
  • Quality and innovation in solution architecture
  • Contribution to AI/data accelerators and GTM assets

Skills

SQL
AWS
ETL
MLOps
MLflow
NLP
Snowflake
Tableau
Azure
Databricks
Google Cloud
Power BI
Python
dbt

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