Description

Key Skills: Python, Spark, Kafka, SQL, Hive, Data Engineering, Big Data, LLM, RAG, GenAI, Distributed Systems, Cloud Platforms

Roles & Responsibilities:

• Lead the architecture and modernization of enterprise-scale data and GenAI platforms.
• Design and develop scalable data pipelines using Python, Spark, Kafka, SQL, and Hive.
• Build and deploy production-grade LLM and Retrieval-Augmented Generation (RAG) solutions.
• Develop batch and real-time data processing systems for large-scale workloads.
• Ensure platform scalability, reliability, performance, and cost optimization.
• Implement best practices for data governance, observability, and security.
• Collaborate with engineering teams to integrate AI and data-driven solutions.
• Drive technical decisions and provide architectural guidance for data and AI initiatives.
• Support cloud-native deployments and platform modernization programs.

Experience Required:

• 14 - 20 years of experience in Data Engineering, Big Data, and GenAI platform development.
• Strong hands-on experience in Python development and data engineering.
• Expertise in Spark, Kafka, SQL, and Hive for large-scale data processing.
• Experience building batch and streaming data pipelines in enterprise environments.
• Hands-on experience with LLMs, Generative AI, and Retrieval-Augmented Generation (RAG).
• Good understanding of distributed systems, cloud-native architectures, and performance optimization.
• Experience designing scalable, secure, and reliable enterprise data platforms.
• Knowledge of data governance, monitoring, and observability practices.
• Experience in Financial Services, FinTech, Product, or E-commerce domains is preferred.
• Strong technical leadership, problem-solving, and stakeholder management skills.

Education: Any Post Graduation, Any Graduation

Key Skills

Education

Any Graduate