Snowflake Presales Architect (Data & AI)

Jade Global • Full-time • San Jose, CA, US • $130k - $180k / year • 12h ago

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 driveend-to-end presales for Data & AI opportunities, combining deep Snowflake knowledge with the ability to positionAI/ML-driven use casesfor enterprise customers.

The role demands a balance oftechnical depth, presales leadership, and innovation mindset, with ~50% billability on strategic engagements.

Key Responsibilities

Leadpresales solutioning for Data, Analytics, and AI-driven opportunitieswith Snowflake at the core
Partner with sales toshape deals and position data + AI solutionsaligned to business outcomes
Design scalable architectures leveragingSnowflake + AI/ML ecosystem (Snowpark, Cortex, external ML platforms)
Conductdiscovery workshopsto identify opportunities forAI/GenAI use cases (e.g., predictive analytics, NLP, automation)
BuildPOCs and demos showcasing AI-infused data platforms
Definedata + AI architecture patterns, including data pipelines, feature engineering, and model integration
Providesolution estimates, sizing, and cost optimization strategies
Act as asolution anchor on delivery (~50% billable)for key programs
Collaborate with partners (Snowflake, cloud, AI ecosystem) to drivejoint GTM initiatives
Contribute toAI accelerators, reusable frameworks, and thought leadership

Required Skills & Qualifications

12+ years inData Engineering / Data Architecture / Analytics
4+ years of strong hands-on experience withSnowflake 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 inpresales / solution consulting roles
Strong understanding of howdata platforms enable AI/ML use cases

AI-Specific Expectations

Working knowledge ofAI/ML concepts(feature engineering, model lifecycle, inference patterns)
Exposure toSnowflake AI capabilities (Snowpark, Cortex)or similar ecosystems
Familiarity withGenAI use cases(LLMs, embeddings, retrieval-augmented generation - RAG)
Ability to positionbusiness-driven AI use cases(customer analytics, personalization, risk/fraud, automation)
Experience integrating data platforms withML frameworks (e.g., Python-based ecosystems, external AI platforms)
Understanding ofdata governance, privacy, and ethical AI considerations