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Snowflake Presales Architect (Data & AI)

Jade Global
Posted 3 months ago, valid for 22 days
Location

San Jose, CA 95103, US

Salary

Competitive

Contract type

Full Time

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Sonic Summary

info
  • The Snowflake Presales Architect role requires a highly skilled professional with 12+ years of experience in Data Engineering, Data Architecture, or Analytics.
  • Candidates must have at least 4 years of hands-on experience with Snowflake implementations and a solid understanding of data warehousing and modern data stacks.
  • The position involves leading presales solutioning for Data and AI-driven opportunities, with a focus on designing scalable architectures and conducting discovery workshops.
  • An understanding of AI/ML concepts and the ability to position business-driven AI use cases is essential for success in this role.
  • The salary for this position is competitive and commensurate with experience, reflecting the advanced expertise required.
Snowflake Presales Architect (Data & AI)1

Role 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 / GCP

  • 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




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