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), Dynamic 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 qualified 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 & AI Engineer (Snowflake & Cortex AI) (India)
🏢 Ironbook AI
📍 India