Senior Technical Architect, Snowflake & AI/ML
Overview
Own technical delivery and outcomes for complex, high-priority customer engagements as the most senior technical voice at Snowflake Services Delivery. Architect end-to-end AI/ML solutions, set standards for scalability and governance, and drive adoption of Cortex, Streamlit in Snowflake, and Snowflake Intelligence. Partner with customer executives to define platform strategy and long-term roadmaps. Mentor junior architects and influence product direction through customer feedback. This role bridges engineering, data science, and business transformation.
What You'll Do9
- 1Lead customer engagements as primary technical authority, owning architecture decisions and driving measurable outcomes across multi-workstream implementations.
- 2Partner with customer executives to define platform strategy, develop long-term roadmaps, and align Snowflake capabilities to business objectives.
- 3Translate ambiguous business problems into scalable technical solutions with clear delivery paths and risk mitigation.
- 4Architect and implement end-to-end AI/ML solutions on Snowflake, setting standards for scalability, performance, security, and operability.
- 5Define and champion MLOps practices covering model deployment pipelines, monitoring, governance frameworks, and lifecycle management.
- 6Drive adoption of Cortex, Streamlit in Snowflake, and Snowflake Intelligence through architecture leadership and hands-on delivery.
- 7Lead replatforming efforts for complex AI/ML workloads onto Snowflake, coordinating across engineering, data science, and platform teams.
- 8Serve as escalation point for technical challenges, unblocking delivery teams and resolving architectural issues.
- 9Mentor junior architects and contribute reusable architecture patterns and delivery accelerators.
Requirements9
- 18+ years in solutions architecture, technical consulting, data engineering, or senior customer-facing technical roles.
- 2Demonstrated track record leading architecture decisions on large-scale enterprise data and AI platforms.
- 3Deep hands-on experience implementing Snowflake in production, including data modeling, performance tuning, security design, and governance.
- 4Expert-level understanding of the full data analytics stack, from ETL pipelines to BI tooling and semantic layers.
- 5Strong grasp of the AI/ML lifecycle: data preparation, feature engineering, model training, deployment, monitoring, and governance.
- 6Proficiency in SQL and Python, with ability to produce and review production-quality code.
- 7Experience designing and implementing MLOps frameworks and model lifecycle management at enterprise scale.
- 8Proven ability to influence senior technical and executive stakeholders.
- 9BA/BS in computer science, engineering, mathematics, or equivalent practical experience.
Salary Insight
$5 - $136k per year
Location
Required Skills
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