Senior Solution Engineer

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. We are looking for a Senior Solution Engineer who thrives at the intersection of data, AI, and complex enterprise architecture. In this role you will work directly with the sales team and channel partners to understand the data challenges of our customers, strategize on how to navigate winning sales cycles, deliver compelling data-driven demonstrations, and support enterprise Proof of Concepts that showcase measurable business outcomes. As a Snowflake Solution Engineer you must share our passion for transforming how organizations use data — from raw ingestion to real-time analytics to AI-powered applications. You thrive in a dynamic environment, are equally comfortable whiteboarding a medallion architecture with a data engineering team and presenting data ROI to a C-suite, and you bring deep opinions about what good data platform design looks like. IN THIS ROLE YOU WILL GET TO: Present Snowflake's Data Cloud vision to data engineering leaders, analytics teams, data scientists, and executive stakeholders at prospects and customers Lead hands-on technical discovery to map a customer's existing data architecture — pipelines, warehouses, lakehouses, governance gaps — and design a Snowflake-native path forward Build and deliver tailored demos and proof of concepts across Snowflake's full data platform: data engineering (Snowpark, Dynamic Tables, Snowpipe), AI/ML (Cortex AI, ML model registry), and data sharing (Data Clean Rooms, Marketplace listings) Guide customers through modern data architecture patterns including Data Mesh, Data Lakehouse, real-time streaming pipelines, and unified governance frameworks Translate ambiguous business problems — churn prediction, supply chain visibility, financial consolidation, operational analytics — into concrete Snowflake data solutions Partner with Product Management, Engineering, and Field teams to feed customer data architecture patterns back into the product roadmap ON DAY ONE WE WILL EXPECT YOU TO HAVE: 7–8 years of industry experience, with a minimum of 5 years in a pre-sales or solutions architecture role focused on data platforms Deep hands-on expertise with SQL, Python, and cloud data warehouse / data lakehouse architectures; able to write working code in a customer session without hesitation Broad experience across the modern data stack: ETL/ELT tools (dbt, Fivetran, Informatica, Spark), streaming platforms (Kafka, Kinesis), orchestration (Airflow, dbt Cloud), BI tools (Tableau, Looker, Power BI), and cloud infrastructure (AWS, Azure, GCP) Proven ability to conduct deep data architecture discovery — understanding a customer's source systems, transformation layers, consumption patterns, and governance requirements — and connect those findings to a Snowflake reference architecture Experience positioning AI and ML capabilities within a data platform context: feature stores, model training pipelines, LLM-powered applications, and AI governance Strong intuition for data governance, quality, and compliance challenges (GDPR, CCPA, PCI) and how platform design decisions affect them Ability to quantify the business value of a modern data architecture — cost reduction, time-to-insight, pipeline reliability, data product monetization A demonstrated track record using AI code