Description

Own the architecture, build, and maintenance of scalable data pipelines for analytics and GenAI applications.

This role is on-site.

Responsibilities

• Design and implement batch and streaming data processing solutions using Spark, Kafka, Hive, and SQL.
• Build and optimize data platform solutions on Databricks to support large-scale environments.
• Implement and support Retrieval-Augmented Generation (RAG) workflows for GenAI use cases.
• Ensure data quality, reliability, security, and performance across all data platforms.
• Define technical best practices and provide leadership for data engineering initiatives.

Required Skills

• 14+ years of experience in Data Engineering, Big Data, and Data Platform development.
• Strong hands-on expertise with Python for data processing and pipeline development.
• Proven experience with Spark, Kafka, Hive, SQL, and Databricks.
• Deep understanding of data lake, lakehouse, and modern data architecture concepts.
• Hands-on experience with LLM, GenAI, and RAG solutions.
• Experience building both batch and real-time data processing systems.
• Knowledge of data governance, security, monitoring, and performance optimization.

Preferred Skills

• Experience in Banking, Fintech, Product, or E-commerce domains.
• Strong stakeholder management and technical leadership skills.

Key Skills

Education

Any Graduate