Base Salary
$128k - $168k/yr
Responsibilities
- Lead customer engagements as the primary technical authority, owning architecture decisions and measurable outcomes across complex implementations.
- Partner with executives and senior technical leaders to define platform strategy, long-term roadmaps, and business-aligned Snowflake solutions.
- Translate ambiguous business problems into scalable technical solutions with clear delivery paths and risk mitigation.
- Serve as the technical escalation point, resolving architectural issues and unblocking delivery teams.
- Architect and implement end-to-end AI/ML solutions on Snowflake with standards for scalability, performance, security, and operability.
- Define and champion MLOps practices covering deployment pipelines, monitoring, governance, and model lifecycle management.
- Drive adoption of Cortex, Streamlit in Snowflake, and Snowflake Intelligence through architecture leadership and hands-on delivery.
- Lead replatforming of complex AI/ML workloads onto Snowflake across customer engineering, data science, and platform teams.
- Connect Services Delivery, Go-to-Market, and product teams while channeling customer feedback into product direction.
- Mentor junior architects and consultants and develop reusable architecture patterns, reference implementations, and delivery accelerators.
Requirements
- Bachelor’s degree in computer science, engineering, mathematics, or a related field, or equivalent practical experience.
- 8+ years of experience in solutions architecture, technical consulting, data engineering, or a senior customer-facing technical role.
- Demonstrated experience leading architecture decisions on large-scale enterprise data and AI platforms.
- Deep hands-on experience implementing Snowflake in production, including data modeling, performance tuning, security design, and platform governance.
- Expertise across the data analytics stack, including ETL, data pipelines, data platform architecture, BI tooling, and semantic layers.
- Strong understanding of the AI/ML lifecycle, including data preparation, feature engineering, model training, deployment, monitoring, and governance.
- Proficiency in SQL and Python, including producing and reviewing production-quality code.
- Experience designing and implementing enterprise-scale MLOps frameworks and model lifecycle management.
- Ability to influence senior technical and executive stakeholders and navigate complex organizational dynamics.
- Preferred experience with generative AI and LLM production use cases, enterprise Centers of Excellence, technology product services organizations, cloud certifications, Snowflake SnowPro Advanced Certification, industry vertical expertise, or multi-team and multi-vendor delivery programs.
About Snowflake
**Snowflake is proud to be the Official Data Collaboration Provider for LA28 and Team USA.** Snowflake delivers the AI Data Cloud — a global network where thousands of organizations mobilize data with near-unlimited scale, concurrency, and performance. Inside the AI Data Cloud, organizations unite their siloed data, easily discover and securely share governed data, and execute diverse analytic workloads. Wherever data or users live, Snowflake delivers a single and seamless experience across multiple public clouds. Snowflake’s platform is the engine that powers and provides access to the AI Data Cloud, creating a solution for data warehousing, data lakes, data engineering, data science, data application development, and data sharing. Join Snowflake customers, partners, and data providers already taking their businesses to new frontiers in the AI Data Cloud.