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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
Most are in India and the US. Here's how to pick the right one for you.
74.689Jobs
17.483IN
79%EN
WorkMundi's database shows 74,689 open sales positions globally. India leads with 17,483 jobs, followed by the US with 13,876. If you're open to geography, you have real options — but the sheer number means you need a filter. Don't apply to everything. Pick a country, a company size, and a sales model that matches what you actually want to do.
Almost 8 in 10 of these ads have their text written in English. That's useful for reading the job description and understanding what you're signing up for. But it tells you nothing about whether the role requires you to speak English with customers, partners, or your team. Ask the hiring manager directly during your first conversation.
The employers posting the most are boxlunch, SIMPLE RECRUIT, FlexBoard, and tmobile. If you see their name on a listing, you know they're actively hiring. That can work in your favor — high-volume recruiters often move faster. But volume also means competition. Your application needs to stand out.
Sales interviews almost always include a version of this: 'Tell me about a time you lost a deal. What did you learn?' Prepare a real story where you take ownership of what went wrong and what you'd do differently. Hiring managers want to see you learn, not just win.