Technical Skills: Data Structures and Algorithms: Expertise in designing efficient data structures and algorithms for big data processing. Distributed Systems: Experience with distributed computing frameworks and parallel processing. Data Integration: Proficiency in integrating data from various sources and ensuring data consistency. Performance Optimization: Skills in optimizing data processing and storage for high performance. Containerization: Experience with Docker and Kubernetes for deploying big data applications. Version Control: Proficiency in using Git for collaborative development. Security: Knowledge of data security practices and compliance with regulatory standards. Machine Learning: Familiarity with machine learning techniques and their application in big data environments Responsibilities: Design, develop, and maintain scalable big data architectures and systems. Implement data processing pipelines using technologies such as Hadoop, Spark, and Kafka. Optimize data storage and retrieval processes to ensure high performance and reliability. Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and deliver solutions. Perform data modeling, mining, and production processes to support business needs. Ensure data quality, governance, and security across all data systems. Stay updated with the latest trends and advancements in big data technologies. Experience with real-time data processing and stream analytics. Knowledge of advanced analytics and data visualization tools. Knowledge of DevOps practices and tools for continuous integration and deployment Experience in managing big data projects and leading technical teams.