We are looking for a Data Engineer / 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

• 
  4–7 years of experience in
  Data Engineering / Analytics Engineering.
• 
  2–4 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.

Requirements

Required Qualifications

• 
  4–7 years of experience in
  Data Engineering / Analytics Engineering.
• 
  2–4 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.