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.