Senior Data Cloud Architect

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🔥 1 hour ago

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Logo of Snowflake

Snowflake

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 (Focus on Acceleration): • Unlock High-Impact Customer Journeys: Identify and prioritize AI/ML customer journeys for SI partner top accounts, focusing on quick wins and high consumption, informed by your understanding of SI partner needs. • Expedited POCs and RFPs: Provide support for partners during RFI/RFP processes and POCs, ensuring rapid turnaround and successful outcomes, informed by your SI proposal experience. • Rapid Deployment Frameworks: Develop and share best practices and POC frameworks specifically designed to accelerate the deployment of prioritized AI/ML customer journeys, based on your SI project implementation knowledge. • SI Partner Snowflake Practice Building (Focus on Production Readiness): • COE for Rapid Implementation: Collaborate on creating and managing Partner Snowflake Centers of Excellence (COE) with a focus on accelerating AI/ML deployments, leveraging your SI center of excellence experience. • Accelerated Capability Maturity: Drive partner capabilities maturity for each AI/ML product category, emphasizing hands-on skills and practical knowledge, informed by your SI skill development experience. • Targeted Communication: Deliver public webinars and product roadmap sessions focused on accelerating AI/ML implementation, drawing on your SI presentation and communication experience. • Work on Initiatives and Joint Solutions with SI partners (Focus on Market-Ready Solutions): • Rapid Joint Solution Development: Build or replatform Partner-led Joint Industry Solutions for AI/ML, focusing on speed to market, based on your SI solution development experience. • Asset Creation for Fast Implementation: Assist partners with asset creation for AI/ML product categories, focusing on templates, code samples, and deployment guides, drawing on your SI asset creation experience. • Customer Journey Alignment for Quick Wins: Align AI/ML customer journeys with Partner Solutions/Offerings, focusing on immediate value and quick wins, informed by your SI customer journey analysis experience. • AI/ML Focused work with SI partners (Hands-On Expertise): • Enable partners to leverage Cortex AI for gen AI customer journeys, including Cortex LLM, Fine Tuning, Search, and Analyst, with a focus on practical application. • Support partners in implementing end-to-end ML development and MLOps using Snowflake ML, emphasizing rapid deployment and operationalization. • Advise partners on using Cortex AI for unstructured data analytics, focusing on real-world customer journeys and quick results.

🎯 Requirements

• REQUIRED: Experience working at a large System Integrator (SI), with a proven track record of accelerating technical wins and production deployments. • PLUS: Knowledge of competitive AI/ML platforms and solutions. • Extensive experience with cloud data platforms, preferably Snowflake. • Hands-on experience with Cloud ML platforms such as Sagemaker, Azure ML, VertexAI, and/or MLFlow. • Experience building and deploying ML model pipelines using serverless and containerized computing including AWS Lambda, Azure Functions, Google Cloud Functions, Docker, Kubernetes etc. • Familiarity with MLOps and CI/CD processes and tools, such as GIT, Azure DevOps, Sagemaker Pipelines, Google Cloud Build • Experience with developing AI/ML use cases including communicating AI/ML strategy and business value • Experience using Big Data or Cloud integration technologies such as Matillion, Azure Data Factory, AWS Glue, AWS Lambda, etc. • Experience in developing and deploying Machine Learning models through the full Data Science life cycle. • Expertise in data science programming languages including Python, SQL, Scala, and/or Spark. • Strong experience with major cloud platforms and tooling, especially Azure, AWS, GCP • Strong CS fundamentals, including proficiency with data structures, algorithms, and distributed systems. • 5+ years industry experience designing, building and supporting large-scale systems with a minimum of 3 years in a pre-sales role. • 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

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