
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.
🕒 August 27
🔔 Pennsylvania – Remote
💵 $136k - $178.5k / year
⏰ Full Time
🟠 Senior
🔙 Backend Engineer
🦅 H1B Visa Sponsor
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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.
• Design robust, scalable AI/ML solutions using the full Snowflake native stack and partner ecosystem • Perform deep-dive Root Cause Analysis for complex system dependencies in AI/ML solutions • Collaborate cross-functionally with Sales and Product teams to align technical roadmaps with customer ROI • Mentor Level 3 architects on MLOps and architectural design best practices • Deconstruct failures in complex pipelines involving external cloud services • Analyze potential failure modes such as model drift and data skew early in the lifecycle • Architect data security and access controls for sensitive AI/ML training data • Reduce post-deployment technical debt and support regional success of complex implementations
• Minimum of 8 years of related experience with a Bachelor's degree (Radford L4 equivalent) • Seasoned professional expertise in resolving wide-ranging issues in creative ways • Strong executive communication; ability to present complex AI/ML concepts and ROI to technical and business audiences • Thorough understanding of the complete Data Science life-cycle, including feature engineering, model development, model deployment, and model management • Experience with GenerativeAI, LLMs, and Vector Databases • Experience with Databricks/Apache Spark • Experience implementing data pipelines using ETL tools • Experience working in a Data Science role • Proven success at enterprise software • Vertical expertise in a core vertical such as FSI, Retail, or Manufacturing • Experience with AWS, Azure, or GCP external cloud services • Knowledge of Snowflake Model Registry, Cortex Functions, Python, and external MLOps tools such as Kubeflow/SageMaker
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