Sr Data Analyst

Birlasoft; Pune District; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Birlasoft in Pune is seeking a Sr Data Analyst with deep expertise in Snowflake Cortex and Databricks AI/ML ecosystem to build enterprise-grade GenAI and analytics solutions.

The role emphasizes hands-on development of AI/ML pipelines, integration with Genie and Agent Bricks, and collaboration with cross-functional teams to translate business problems into AI-driven outcomes.

Qualifications

• Hands-on experience with Snowflake Cortex and Databricks Mosaic AI.
• Experience with Genie and Agent Bricks for AI agents.
• Ability to design end-to-end AI/ML solutions.

Responsibilities

• Design and develop end-to-end AI/ML and GenAI solutions using Snowflake Cortex and Databricks Mosaic AI.
• Build intelligent applications with Databricks Genie and Agent Bricks for conversational analytics.
• Develop scalable feature engineering pipelines on modern data platforms.
• Implement LLM-based use cases including RAG and embeddings.
• Collaborate with cross-functional teams to translate business problems into AI-driven solutions.

Skills

GenAI

LLMs

Data Analytics

Feature Engineering

Cross-functional collaboration

Tools

Snowflake Cortex

Databricks Mosaic AI

Databricks Genie

Agent Bricks

Embeddings

Job description

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Location: INDIA - PUNE - BIRLASOFT OFFICE - HINJAWADI

Title: Sr Data Analyst

Description:

Short Description

Position Overview:

We are seeking a highly skilled Data Scientist with deep expertise in Snowflake and Databricks AI/ML ecosystem. Mandatory hands‑on experience in Snowflake Cortex and Databricks Mosaic AI, Genie, and Agent Bricks is required to build enterprise‑grade GenAI and advanced analytics solutions.

Key Responsibilities

• Design and develop end-to-end AI/ML and GenAI solutions leveraging Snowflake Cortex and Databricks Mosaic AI ecosystem.
• Build intelligent applications using Databricks Genie and Agent Bricks for conversational analytics and AI agents.
• Develop scalable feature engineering pipelines using modern data platforms.
• Implement LLM-based use cases including RAG, embeddings, and AI assistants.
• Collaborate with cross-functional teams to translate business problems into AI-driven solutions.

Area(s) of responsibility

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