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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 Senior Product Manager for Data Observability will define product strategy, lead cross-functional teams, and oversee development of AI-powered data monitoring and quality solutions.

As an Engineering Manager for Transformation & Data Lake at Snowflake, you'll lead efforts in building interoperable data solutions, focusing on metadata, integration platforms, and data pipeline automation, driving innovation across cloud data ecosystems.

Lead a team of engineers to design and develop AI-powered migration products, ensuring quality delivery while fostering innovation and supporting team growth.

The Account Executive will drive new business and expand existing accounts, become a product expert, deliver presentations, develop sales strategies, and meet sales quotas in the enterprise market.

Lead Snowflake implementation and services delivery for complex, technical projects. Own client relationships, manage project scope/schedule/risks, identify upsell opportunities, enable sales, and drive process and product improvements across teams.

Customer-facing technical role supporting AI/ML initiatives across US Major Accounts. Architect and prototype AI/ML solutions, build MVPs and PoCs, support regional SE teams, deliver technical presentations and workshops, and upskill teams. Travel ~30-40% to support customer engagements.

Lead large, complex Snowflake implementations and cloud data programs as the program lead for Fortune 500 customers. Drive vision, roadmap, risk mitigation, budget governance, data migrations, and executive stakeholder alignment to deliver on-time, on-budget outcomes and measurable customer value.

In this role, you will lead the AI engineering lifecycle for Snowflake Database Engineering products, enhancing workflows and collaborating to address customer needs.

Lead end-to-end product lifecycle for enterprise AI services: define vision and roadmap, engage customers, drive cross-functional execution with engineering, design, and GTM to scale bespoke AI solutions into repeatable platform features.