Description

You will build and maintain the data infrastructure necessary to support AI and analytics workloads.

Responsibilities

• Design, develop, and maintain scalable ETL/ELT data pipelines for AI and analytics.
• Implement real-time and batch data processing architectures using Spark, Kafka, and Snowflake.
• Collaborate with Data Scientists and ML Engineers to optimize and deploy AI/ML models in production.
• Manage data platform and warehouse solutions on Azure cloud platforms.
• Design and manage GenAI models, agentic workflows, and frameworks like LangChain, LangGraph, or LlamaIndex.
• Automate data workflows using CI/CD pipelines and Infrastructure-as-Code.
• Monitor and optimize data infrastructure for performance, security, and reliability.

Required Skills

• 8+ years of experience in data engineering.
• Expertise in ETL/ELT data pipeline development.
• Proficiency with Apache Spark and Kafka.
• Experience with Snowflake.
• Strong data modeling skills using ER, structured, and NoSQL schema definitions.
• Experience working with both structured and unstructured data.
• Hands-on experience with CI/CD pipelines.
• Ability to implement AI/GenAI-powered data transformation processes.
• Knowledge of data security, compliance, and governance best practices.

Key Skills

Education

Any Graduate