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Senior Solution Engineer

Snowflake Inc.· Solution Engineering
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US-NY-New York$165k - $216.6kFull-timePosted 6mo ago

About the role

Senior Solution Engineer at Snowflake focused on data, AI, and enterprise architecture. Engage with sales and partners to map customer data challenges, design Snowflake-native solutions, deliver data-driven demonstrations, and support enterprise proofs-of-concept to 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 — 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

Qualifications

  • 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 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. A Master's in Data Science or Business Analytics is a plus
  • Experience working with GSIs (EY, Deloitte, Accenture, Slalom, etc.) on large data platform programs is beneficial but not required

Skills

Required:SQLPythonCloud data warehouse / data lakehouse architecturesETL/ELT toolsStreaming platformsOrchestrationBI tools
Nice to have:AI/ML capabilities in data platform

Benefits

  • Snowflake offers competitive base salary, variable compensation, equity, and comprehensive benefits including 401(k), health/dental/vision, flexible PTO, and professional development budget.
Last updated Aug 27, 2026. Interested? Apply on the company site.

About Snowflake Inc.

The Data Platform Built for Data Teams.

Snowflake powers AI, data engineering, applications, and analytics on a trusted, scalable AI Data Cloud—eliminating silos and accelerating innovation.

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