AI Engineer

• We are looking for AI Engineer with strong hands-on experience in Snowflake Data Warehouse and exposure to AI-driven analytics solutions.
• The role focuses on building scalable data pipelines, implementing optimized data models, and contributing to AI-powered applications such as conversational analytics using Snowflake Cortex LLM.
• This is a delivery-focused role with growing technical ownership and business exposure.

Key Responsibilities

1. Snowflake Data Engineering

• Develop and maintain data models (Star schema / Snowflake schema).
• Build and optimize ELT pipelines within Snowflake.
• Write efficient SQL transformations and performance-tuned queries.
• Support data ingestion from structured and semi-structured sources.
• Assist in warehouse sizing, clustering, and cost optimization.
• Implement role-based access control (RBAC) and basic data governance practices.

2. AI & Cortex LLM Implementation Support

• Support development of AI agents using Snowflake Cortex LLM.
• Assist in building Retrieval-Augmented Generation (RAG) workflows.
• Work on vector embeddings and semantic search implementations.
• Participate in prompt engineering and testing.
• Validate and test AI-generated outputs for accuracy and security.

3. Conversational & Analytics Solutions

• Contribute to building conversational analytics tools enabling natural language queries.
• Support integration of data models with BI tools (Power BI / Tableau).
• Translate functional KPIs into data models and dashboards.
• Ensure data accuracy, consistency, and performance.

4. Collaboration & Delivery

• Work closely with Senior Leads and Architects on design implementation.
• Participate in sprint planning and Agile ceremonies.
• Document data models, transformations, and solution components.
• Provide production support and troubleshooting.

Required Qualifications

• 5–7 years of experience in Data Engineering / Analytics Engineering.
• 3–4 years hands-on experience with Snowflake.
• Strong SQL expertise (advanced joins, window functions, performance tuning).
• Working knowledge of Python.
• Understanding of data modeling concepts (Dimensional modeling preferred).
• Exposure to AI/LLM platforms (Snowflake Cortex or similar is a plus).
• Experience integrating with BI tools (Power BI / Tableau).

Preferred Qualifications

• Exposure to RAG frameworks or semantic search.
• Basic understanding of data governance and security models.
• Experience working with semi-structured data (JSON, Parquet, etc.).
• Domain exposure in HR, Sales, Finance, or Supply Chain analytics.