Description

You will architect and modernize enterprise-scale data and GenAI platforms, ensuring scalability, reliability, and cost optimization.

This role is on-site.

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.
• Implement best practices for data governance, observability, and security.

Required Skills

• 14+ years of experience in Data Engineering, Big Data, and GenAI platform development.
• Strong hands-on expertise in Python, Spark, Kafka, SQL, and Hive.
• Proven experience building batch and streaming data pipelines in enterprise environments.
• Hands-on experience with LLMs, Generative AI, and RAG architectures.
• Deep 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.

Preferred Skills

• Experience in Financial Services, FinTech, Product, or E-commerce domains.
• Strong technical leadership, problem-solving, and stakeholder management skills.

Key Skills

Education

Any Graduate