Position Overview We are seeking an experienced, hands-on Senior Data & AI Engineer with 6 to 8 years of proven experience in advanced data engineering and enterprise AI application development. In this role, you will bridge the gap between enterprise data warehouse architecture and cutting-edge generative AI / agentic workflows directly on the Snowflake Data Cloud. The ideal candidate possesses intermediate-to-advanced expertise in Snowflake data engineering, combined with specialized, hands-on experience developing autonomous agents, Model Context Protocol (MCP) interfaces, and leveraging Snowflake Cortex AI (including Cortex Search and Cortex Analyst). You will build secure, governed, high-throughput analytical data pipelines while orchestrating intelligent AI agents that integrate seamlessly across internal Snowflake resources and external AI frameworks.

Key Responsibilities
A. Agentic AI & Snowflake Cortex Engineering
• Design, implement, and deploy production-grade AI Agents utilizing Snowflake Cortex AI, Cortex Analyst, and Cortex Search.
• Architect and build Model Context Protocol (MCP) servers and clients in Snowflake to expose enterprise datasets and tools to generative AI agents.
• Create, curate, and optimize semantic models (YAML/YAML schemas) used by Cortex Analyst to achieve deterministic, reliable Text-to-SQL precision.
• Integrate Snowflake-native AI agents with external enterprise agent frameworks (e.g., LangChain, LlamaIndex, CrewAI, AutoGen) and third-party APIs.
• Implement retrieval-augmented generation (RAG) pipelines inside Snowflake using Cortex Search over structured, semi-structured, and unstructured data. B. Snowflake Data Engineering & Platform Architecture
• Build, deploy, and monitor scalable, resilient ELT pipelines using Snowpark (Python), Agile Tables, Streams, and Tasks.
• Optimize Snowflake compute, virtual warehouse sizing, caching, cluster keys, and query performance to maintain low latency and cost-effectiveness.
• Design and implement unified data models (Medallion architecture: Bronze, Silver, Gold layers)



that serve both BI reporting and real-time agent retrieval.
• Lead migration and modernization patterns for integrating diverse external source systems into Snowflake via zero-copy cloning, data shares, and external stages. C. Enterprise Data Governance & Security
• Implement robust data governance strategies using Snowflake Horizon capabilities, including tag-based masking, row access policies, and data classification.
• Ensure strict data isolation and context boundary controls so that AI agents and LLM invocations respect end-user role-based permissions (RBAC).
• Monitor query audits, data lineage, and model execution trails via Snowflake Access History and Account Usage views.
• Enforce secure credential handling and integration points for external API calls and third-party model orchestrations. D. Data Analysis & Cross-Functional Collaboration
• Collaborate closely with data analysts, product managers, and business stakeholders to translate domain requirements into high-value data & AI solutions.
• Conduct deep-dive exploratory data analysis to evaluate data quality, anomalies, and structural integrity prior to AI agent ingestion.
• Provide mentorship, technical leadership, and architectural reviews for data engineers and analytics developers. Required Qualifications & Prerequisites
• Total

Experience:
6 to 8 years of professional experience in data engineering, data warehousing, and distributed data systems.
• Hands-on Snowflake Mastery (Intermediate to Advanced):
• Demonstrated hands-on experience with Snowpark (Python), Stored Procedures, UDFs, UDTFs, Dynamic Tables, Streams, and Tasks.
• In-depth understanding of Snowflake storage architecture, micro-partitioning,



query profile debugging, and warehouse credit optimization.
• Cortex AI & Agentic AI Specialization:
• Hands-on experience designing and operating AI agents and Model Context Protocol (MCP) integrations within or connected to Snowflake.
• Direct production experience with Snowflake Cortex AI features: Cortex Analyst, Cortex Search, Cortex LLM functions (COMPLETE, EXTRACT_ANSWER, SUMMARIZE), and semantic specification authoring.
• Multi-Agent & AI Integration:
• Experience integrating Snowflake data and Cortex services with external agent frameworks (e.g., LangChain, LlamaIndex, Semantic Kernel, CrewAI).
• Solid understanding of tool-calling, function calling, structured outputs, prompt engineering, and context window management for enterprise LLMs.
• Governance, Security & Compliance:
• Hands-on experience with Snowflake Data Governance: Row Access Policies, Column Masking Policies, Object Tagging, and Data Clean Rooms.
• Strong understanding of security protocols, OAuth, JWT, and network policies within enterprise cloud environments.
• Data Analytics & Modeling:
• Expert-level SQL proficiency (window functions, recursive CTEs, query plan optimization).
• Solid background in dimensional modeling, data vault, or medallion pipeline architecture for self-service analytics.
• Software Engineering Practices:
• Proficiency in Python (Object-Oriented, asynchronous programming, testing frameworks).
• Experience with modern CI/CD, Git, dbt (data build tool), and Terraform / Snowflake infrastructure-as-code. Preferred / Nice-to-Have Qualifications
• Snowflake SnowPro Advanced Certification (e.g., SnowPro Advanced: Data Engineer or Architect).
• Experience deploying Streamlit in Snowflake (SiS) or custom React frontends interacting with Snowflake AI endpoints.
• Familiarity with containerized workloads using Snowpark Container Services (SPCS).
• Experience with vector databases, hybrid search architectures, and fine-tuning open-weights models.

📌 Senior Data (India)
🏢 Ironbook AI
📍 India