Design data partitioning, caching strategies, and data models that utilize Redis and Gemfire effectively to enhance system performance and response times.
Develop high-level and low-level architectural documentation, including diagrams, design patterns, and technical specifications.
Implement Redis clustering, replication, and sharding strategies for high availability, data redundancy, and fault tolerance.
Design and implement cache eviction policies, expiration times, and data synchronization mechanisms to ensure the cache remains efficient and up to date.
Collaborate with developers to implement robust connection pooling, error handling, and optimized communication with Redis.
Qualifications:
Bachelor's or Master's degree in Computer Science, Software Engineering, or a related field.
Extensive hands-on experience with Redis, including clustering, replication, sharding, and cache design
Strong understanding of data structures, algorithms, and distributed systems concepts and Big Data Solutions.
Proficiency in designing for scalability, availability, and performance optimization.
Proficiency in Gemfire caching technology.
Hands-on experience with automation and scripting (Python, Bash, or PowerShell).
Excellent communication and collaboration skills to work effectively with cross-functional teams.
Knowledge of cloud platforms (e.g., AWS, Azure, GCP) and containerization technologies is a plus.
