Senior Technical Architect

🔥 1 hour ago

🏄 California – Remote

🏄 California – Remote

💵 $160k - $210k / year

⏰ Full Time

🟠 Senior

🔙 Backend Engineer

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Snowflake

WebsiteLinkedInAll Job Openings

5001 - 10000 employees

Founded 2012

💼 Consulting

📣 Marketing

Consulting • Marketing • Cloud Computing

Snowflake is a cloud-based data-warehousing company that provides a platform for data storage, processing, and analytics. It allows businesses to store data in a centralized location and perform complex queries and analytics on that data efficiently. Snowflake is designed to handle a wide range of data workloads and can scale dynamically to meet the needs of growing businesses.

📋 Description

• Lead customer engagements as the primary technical authority, owning architecture decisions and driving measurable outcomes across complex, multi-workstream implementations • Partner with customer executives and senior technical leadership to define platform strategy, develop long-term roadmaps, and align Snowflake capabilities to business objectives • Architect and implement end-to-end AI/ML solutions on Snowflake, setting standards for scalability, performance, security, and operability across the customer's environment • Define and champion MLOps practices within customer organizations, covering model deployment pipelines, monitoring, governance frameworks, and lifecycle management • Drive adoption of Snowflake's AI product suite (Cortex, Streamlit in Snowflake, Snowflake Intelligence) through architecture leadership and hands-on delivery

🎯 Requirements

• BA/BS 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 • Deep hands-on experience implementing Snowflake in production environments, including data modeling, performance tuning, security design, and platform governance • Expert-level understanding of the full data analytics stack, from ETL and data pipelines to data platform architecture, BI tooling, and semantic layers • Strong grasp of the AI/ML lifecycle, from data preparation and feature engineering through model training, deployment, monitoring, and ongoing governance • Proficiency in SQL and Python; ability to produce and review production-quality code as part of delivery leadership • Experience designing and implementing MLOps frameworks and model lifecycle management at enterprise scale • Proven ability to influence senior technical and executive stakeholders and navigate complex organizational dynamics.

🏖️ Benefits

• Health insurance • Professional development opportunities • Flexible working hours