Senior Solution Engineer

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.

Responsibilities

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 and design a Snowflake-native path forward; Build and deliver tailored demos and proof of concepts across Snowflake's full data platform; Guide customers through modern data architecture patterns including Data Mesh, Data Lakehouse, real-time streaming pipelines, and unified governance frameworks; Translate ambiguous business problems into concrete Snowflake data solutions; Partner with Product Management, Engineering, and Field teams to feed customer data architecture patterns back into the product roadmap; Work directly with the sales team and channel partners to understand customer data challenges, strategize on winning sales cycles, and support enterprise Proof of Concepts

Requirements

3–8 years of industry experience 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; 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 and connect 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 generation tools to accelerate prototyping and proof-of-concept delivery; University degree in computer science, data science, engineering, mathematics or a related field, or equivalent practical experience; Must be in North Carolina or South Carolina

Nice to have

Master's in Data Science or Business Analytics; Experience working with GSIs (EY, Deloitte, Accenture, Slalom, etc.) on large data platform programs

Benefits

Competitive base salary; variable compensation; equity; comprehensive benefits; 401(k); health/dental/vision; flexible PTO; professional development budget