Senior Lead – Snowflake & AI Engineering

Key Responsibilities

1. Snowflake Data Architecture & Modeling

• Design scalable, performance-optimized data models on Snowflake (Star schema, Snowflake schema, Data Vault).
• Build and optimize ELT pipelines using Snowflake-native capabilities.
• Implement data governance, security policies, and role-based access control (RBAC).
• Perform performance tuning, clustering optimization, and warehouse sizing strategies.
• Ensure cost-efficient Snowflake implementation.

2. AI & Snowflake Cortex LLM Implementation

• Develop and deploy AI agents using Snowflake Cortex LLM.
• Design and implement Retrieval-Augmented Generation (RAG) frameworks grounded on enterprise data.
• Build vector embeddings, semantic search layers, and contextual response frameworks.
• Apply prompt engineering and guardrails for enterprise AI use cases.
• Ensure AI outputs are explainable, secure, and business-aligned.

3. Conversational Insights Development

• Build conversational analytics solutions enabling natural language interaction with enterprise datasets.
• Deliver persona-based insights tailored to functional stakeholders.
• Integrate structured and semi-structured data into unified analytics models.
• Collaborate with UI/BI teams for dashboard and insight delivery.

4. Technical Leadership & Delivery Ownership

• Lead a small team (3–6 engineers) and provide architectural guidance.
• Review code, enforce best practices, and ensure quality standards.
• Own end-to-end delivery from requirements to deployment.
• Participate in effort estimation, sprint planning, and stakeholder communication.
• Mentor junior engineers on Snowflake and AI implementation.

5. Business & Functional Collaboration

• Translate functional requirements from HR, Sales, Finance, and Supply Chain into scalable data solutions.
• Build KPI frameworks and analytical models aligned to business goals.
• Identify automation opportunities using AI-driven insights.

Required Qualifications

• 7–10 years of experience in Data Engineering / Analytics Engineering / AI Engineering.
• 4+ years hands-on experience with Snowflake Data Warehouse.
• Strong expertise in data modeling (Dimensional modeling preferred).
• Hands-on experience with Snowflake Cortex LLM or similar LLM platforms.
• Experience building RAG-based or conversational AI solutions.
• Strong SQL and Python skills.
• Understanding of data governance, security, and performance optimization.
• Experience working in Agile delivery environments.

Preferred Qualifications

• Snowflake certification.
• Experience with BI tools (Power BI / Tableau).
• Exposure to MLOps and model deployment practices.
• Domain knowledge in at least two functional areas (HR, Sales, Finance, Supply Chain).