Principal Data Cloud Architect

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🔥 4 minutes ago

🏄 California – Remote

🏄 California – Remote

💵 $189k - $248.1k / year

⏰ Full Time

🔴 Lead

☁️ Cloud Engineer

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Snowflake

WebsiteLinkedInAll Job Openings

5001 - 10000 employees

Founded 2012

☁️ SaaS

🏢 Enterprise

🤝 B2B

SaaS • Enterprise • B2B

Snowflake is a cloud-based data platform and data warehouse-as-a-service. It enables organizations to store, process, analyze, and share large volumes of structured and semi-structured data across multiple clouds, with separated scalable compute and storage, built-in security and data-sharing capabilities, and support for analytics and machine-learning workloads. Snowflake is delivered as a managed SaaS offering for enterprise customers and is primarily marketed and sold as a B2B product.

📋 Description

• Strategic Account Alignment with top accounts for SI partners • Identify and prioritize AI/ML customer journeys for SI partner top accounts • Provide support for partners during RFI/RFP processes and POCs • Develop and share best practices and POC frameworks • Collaborate on creating and managing Partner Snowflake Centers of Excellence (COE) • Drive partner capabilities maturity for each AI/ML product category • Deliver public webinars and product roadmap sessions • Build or replatform Partner-led Joint Industry Solutions for AI/ML • Assist partners with asset creation for AI/ML product categories • Align AI/ML customer journeys with Partner Solutions/Offerings • Enable partners to leverage Cortex AI for gen AI customer journeys • Support partners in implementing end-to-end ML development and MLOps • Advise partners on using Cortex AI for unstructured data analytics • Mentor and guide junior cloud architects in critical AI/ML engagements

🎯 Requirements

• Experience working at a large System Integrator (SI) • Knowledge of competitive AI/ML platforms and solutions • Extensive experience with cloud data platforms, preferably Snowflake • Hands-on experience with Cloud ML platforms (Sagemaker, Azure ML, VertexAI, MLFlow) • Experience building and deploying ML model pipelines using serverless and containerized computing (AWS Lambda, Azure Functions, Google Cloud Functions, Docker, Kubernetes) • Familiarity with MLOps and CI/CD processes and tools (GIT, Azure DevOps, Sagemaker Pipelines, Google Cloud Build) • Experience developing AI/ML use cases and communicating AI/ML strategy and business value • Experience with Big Data or Cloud integration technologies (Matillion, Azure Data Factory, AWS Glue, AWS Lambda) • Experience developing and deploying Machine Learning models through the full Data Science life cycle • Expertise in data science programming languages (Python, SQL, Scala, Spark) • Strong experience with major cloud platforms (Azure, AWS, GCP) • Strong CS fundamentals (data structures, algorithms, distributed systems) • 10+ years industry experience • BS/MS/PhD in Computer Science or related majors

🏖️ Benefits

• medical, dental, vision, life, and disability insurance • 401(k) retirement plan • flexible spending & health savings account • at least 12 paid holidays • paid time off • parental leave • employee assistance program • other company benefits