Snowflake Cortex SPCS Data Engineer

• Strong hands-on experience with Snowflake and working knowledge of Streamlit. 
• Working Knowledge Cortex Analyst and AI/ML capabilities.   
• Basic knowledge in Python for data engineering, automation, and API integration.   
• Experience building interactive applications using Streamlit or similar frameworks.   
• Deep understanding of semantic modeling, logical tables, and verified queries in Snowflake.   
• Familiarity with LLMs, generative AI, and conversational interfaces.   
• Knowledge of RESTful API design and integration.   
• Experience with RBAC, data governance, and secure data handling practices.  
• Data Engineering, ETL / ELT, Incremental data processing, Dimensional modelling, Stored Procedures. 
• Snowflake, Advanced SQL, LLM Prompt Engineering, LLM Response Tuning 
• Experience with Snowflake Cortex Analyst, Snowflake Semantic Views, Snowflake Cortex Search, Snowflake Cortex Agents, Semantic modelling, Natural-language-to-SQL solutions, RAG / semantic retrieval concepts. 
• Configure, manage, and enhance Cortex Search indexes to enable intelligent enterprise document search and AI-assisted knowledge discovery. 
• Develop AI-powered applications and assistants using Python, Snowpark, APIs, and Streamlit-in-Snowflake/ Integration with React.js frontEnd 
• Lead migration and modernization of existing AI solutions into the Snowflake AI Data Cloud ecosystem. 
• Implement document intelligence capabilities using Snowflake Document AI for extraction, classification, and knowledge retrieval from unstructured content. 
• Snowpark Container Services (SPCS) deployment, management, and monitoring.
• Docker and containerization technologies.
• Python programming for data engineering and AI/ML workloads.
• Integration of Snowflake with APIs, enterprise applications, and data ingestion tools.
• Experience with cloud platforms such as AWS, Azure, or GCP.
• Snowflake security, RBAC, data access controls, and governance.
• Git-based source control and CI/CD pipeline implementation.
• Troubleshooting, production support, performance optimization, and cost management.
• Ability to design and deliver end-to-end data and AI solutions independently.
• Integrate AI solutions with enterprise data platforms, SharePoint repositories, APIs, and business applications. 

Desirable Skills

• Kubernetes and container orchestration concepts to support advanced SPCS deployments.
• Knowledge of ML lifecycle management, model monitoring, and MLOps practices.
• Experience building end-to-end GenAI applications
• Understanding of vector databases, embeddings, and knowledge graph concepts.
• Experience with Infrastructure as Code (Terraform) and automated cloud deployments.
  • Snowflake AI, SnowPro Advanced, or Cloud Platform certifications.