Jobs at Snowflake

Lead acquisition and management of strategic Financial Services partners, create and execute GTM plans, drive partner and customer adoption of Financial Services products, and collaborate cross-functionally with Sales, GTM, Marketing, Operations, and Product to grow Snowflake’s Data Cloud ecosystem.

Provide legal support for commercial transactions, negotiate agreements, advise senior leaders, manage risk, and streamline contracting processes in a fast-paced environment.

The role involves leading customer discussions on AI strategy, designing scalable AI solutions, and supporting enterprise Proof of Concepts. The engineer will translate technical concepts into business outcomes while navigating sales dynamics.

The Senior Professional Services Solutions Architect will drive sales and delivery of Snowflake services, acting as a trusted advisor while collaborating with customers to solve their data challenges.

Lead a team of industry technical architects to drive strategic customer engagements and build repeatable reference architectures for the Snowflake AI Data Cloud. Partner with Sales, Engineering, and Marketing to translate persona-driven use cases into measurable business outcomes, run design-led workshops, create solution showcases, influence product roadmaps, and scale engagement models globally.

The RVP, Priority Support Engineering at Snowflake leads paid support offerings, manages customer relationships, drives revenue, and operates AI-natively to enhance customer support and engagement, while building and scaling the team.

The Cloud Partner Solutions Engineer drives partner success by managing cloud integration strategies, leading joint GTM plans, and executing co-sell initiatives across AWS, Azure, and GCP, ensuring measurable value and customer outcomes.

The Data Platform Architect will lead technical efforts in designing Snowflake's data solutions for enterprise clients, collaborating with sales, presenting to executives, and integrating complex data technologies.

Lead sales and deployment of custom AI/ML solutions, driving pipeline and revenue for allocated accounts. Collaborate with Field Sales, Product, Sales Engineering and AI teams to discover requirements, architect agentic AI solutions, write SOWs, negotiate commercial terms, and manage complex sales cycles to ensure customer adoption and measurable business outcomes.

Lead Snowflake's GTM partnership with AWS by developing strategy, accelerating co-sell revenue and joint pipeline, enabling field engagement, driving AWS Marketplace and Partner Central adoption, aligning solutions with AWS priorities, and delivering scalable enablement and escalation support across cross-functional teams.

Build net-new enterprise business across Malaysia by prospecting, conducting discovery and demos, creating and qualifying pipeline, developing executive relationships, executing territory and sales strategies, closing complex deals, and collaborating with partners and cross-functional teams to meet quarterly and annual quotas.

The Senior Solution Engineer will solve complex customer problems, support sales cycles, conduct technical demonstrations, and collaborate on product improvements, leveraging experience in database technologies and AI.

Lead global support operations to transform manual processes into AI-augmented, outcome-based systems. Drive staffing, tiered support models, capacity planning, data-driven improvements, and cross-functional initiatives to improve customer experience and operational efficiency. Build and empower teams, define success metrics, and institutionalize support intelligence at scale.

The Solution Engineer - Data Engineering Specialist will provide technical leadership in the financial services sector, collaborating with sales teams to demonstrate Snowflake's data platform capabilities while engaging with technical and executive stakeholders.

Serve as an AI/ML-focused solution engineer for Healthcare & Life Sciences: provide technical guidance, design cloud data and lakehouse architectures on Snowflake, lead demos and proofs-of-concept, support sales cycles, collaborate with product and engineering, and communicate AI/ML value to technical and executive stakeholders.