Lead Snowflake Architect (Azure & Agentic AI)

Position Overview

We are seeking a Principal Data Architect with 15–20+ years of deep technology leadership experience to drive the enterprise Snowflake and Azure Data Cloud roadmap for global Financial Services operations.

The ideal candidate will combine elite hands-on expertise in Snowflake on Azure with cutting-edge knowledge of Agentic AI—leveraging AI agents to modernize Data Engineering, streamline the SDLC, and orchestrate enterprise data pipelines.

Key Responsibilities

• Enterprise Architecture & Strategy: Shape and execute the multi-year enterprise Azure-Snowflake roadmap, architecture blueprints, data modeling standards, and cloud migration strategies.
• Agentic AI & Data Engineering Integration: Design and deploy AI Agents and autonomous workflows for Data Engineering (e.g., Snowflake Cortex AI, Cortex Search/Analyst, automated SQL generation, and intelligent data pipeline orchestration).
• Agentic SDLC Optimization: Implement AI-driven automation across the Software Development Life Cycle (automated code validation, intelligent CI/CD pipelines, automated data quality checks, and AI-driven documentation).
• Azure Cloud Data Architecture: Lead end-to-end integration of Snowflake within the Microsoft Azure ecosystem (Azure Data Factory, Azure AD/Entra ID, Azure Blob/ADLS, Azure Event Hubs).
• Migration & Governance: Oversee complex enterprise migrations from legacy data warehouses to Azure Snowflake, ensuring strict compliance, Role-Based Access Control (RBAC), and FinOps cost optimization.
• Technical Leadership & Client Stakeholder Engagement: Act as the primary strategic advisor to enterprise leadership, translating complex business demands into scalable, resilient cloud data architectures.

Required Qualifications & Experience

• Total Experience: 15 to 20+ years in IT, Data Engineering, and Enterprise Software Architecture.
• Architectural Leadership: 7+ years as a Principal/Lead Data Architect designing enterprise-grade Snowflake data warehouses on Microsoft Azure.
• Agentic AI & Automation: Demonstrated hands-on experience or architecture leadership in Agentic AI, LLM orchestration frameworks (LangChain, LlamaIndex, AutoGen), and Snowflake Cortex AI.
• Modern Data Stack: Expertise in dbt, Azure Data Factory (ADF), PySpark, Python, SQL, and automated data pipeline frameworks.
• SDLC & DevOps: Proven track record of automating data delivery pipelines, CI/CD for data applications, and embedding AI tooling into standard engineering practices.
• Domain Knowledge: Prior experience in Financial Services, Banking, or Large-Scale Enterprise Transactional Data environments is strongly preferred.