Description

Key Skills: Python, Spark, Kafka, Hive, SQL, Databricks, Data Engineering, LLM, RAG, GenAI, Big Data, Data Pipelines

Roles & Responsibilities:

• Design, build, and maintain scalable data pipelines for analytics and GenAI applications.
• Develop batch and streaming data processing solutions using Spark, Kafka, Hive, and SQL.
• Implement and support Retrieval-Augmented Generation (RAG) workflows for GenAI use cases.
• Build and optimize data platform solutions on Databricks.
• Ensure data quality, reliability, security, and performance across data platforms.
• Integrate LLM-based applications with enterprise data sources.
• Monitor, troubleshoot, and improve data processing workflows.
• Collaborate with cross-functional teams to deliver scalable data and AI solutions.
• Define best practices and provide technical leadership for data engineering initiatives.

Experience Required:

• 14 - 20 years of experience in Data Engineering, Big Data, and Data Platform development.
• Strong hands-on experience with Python for data processing and pipeline development.
• Experience working with Spark, Kafka, Hive, SQL, and Databricks in large-scale environments.
• Good understanding of data lake, lakehouse, and modern data architecture concepts.
• Hands-on experience with LLM, GenAI, and Retrieval-Augmented Generation (RAG) solutions.
• Experience building batch and real-time data processing systems.
• Knowledge of data governance, security, monitoring, and performance optimization.
• Experience working in Banking, Fintech, Product, or E-commerce domains is preferred.
• Strong problem-solving, stakeholder management, and technical leadership skills.

Education: Any Graduation /Any Post Graduation

Key Skills

Education

Any Graduate