
5001 - 10000 employees
Founded 2012
âď¸ SaaS
đ˘ Enterprise
đ¤ 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.
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5001 - 10000 employees
Founded 2012
âď¸ SaaS
đ˘ Enterprise
đ¤ 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.
⢠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.
⢠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.
⢠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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