Job highlights

- Experience in Snowflake engineering, Azure Data Factory, AI/GenAI, advanced SQL, and data architecture

- Design and develop Snowflake data models and ADF pipelines, build AI solutions, lead technical design and delivery, mentor teams, and manage production stability

Key Responsibilities

Snowflake Engineering

- Design and develop scalable Snowflake data models, warehouses and data products.

- Develop and optimize SQL, views, agile tables, stored procedures and Snow sql based transformations

- Develop reconciliation and RLS frameworks.

Azure Data Factory

- Design and build metadata-driven ADF pipelines for batch and incremental integration.

- Integrate enterprise applications, APIs, files, Azure storage and Snowflake using secure, supportable patterns.

- Pipeline migration activities with dependency assessment, regression testing, controlled rollout and rollback readiness.

- Implement monitoring, alerting, retry,



exception handling and operational dashboards.

Snowflake Cortex AI and GenAI

- Develop Eaton-relevant AI solutions using Snowflake Cortex AI capabilities.

Technical Leadership and Delivery

- Translate business requirements into architecture, technical designs, delivery estimates and implementation plans.

- Lead design reviews, code reviews, engineering standards and technical documentation.

- Mentor engineers and coordinate work across data, application, cloud, security, testing and support teams.

- Own defect resolution, root-cause analysis, release readiness and production stabilization.

- Communicate risks, dependencies, decisions and delivery status

Required Technical Skills

- Snowflake

- Azure Data Factory

- AI / GenAI

- Programming

- Data Architecture

- DevOps

📌 Snowflake Data Engineer (Pune)
🏢 Tata Consultancy Services
📍 Pune