Data Engineer Revalsys Technologies
Revalsys Technologies
Office Location
Full Time
Experience: 3 - 3 years required
Pay:
Salary Information not included
Type: Full Time
Location: Hyderabad
Skills: Data Engineering, Performance optimization, Data Modeling, Python, Bash Scripting, Dashboarding, NoSQL, spark, Kafka, Apache Cassandra, CRUD Operations, data sharding
About Revalsys Technologies
Job Description
We are looking for an experienced Data Engineer specializing in Apache Cassandra to oversee the processing of large-scale data. The ideal candidate will have a proven track record in managing crores of records, with a specific focus on high-performance CRUD operations, efficient data retrieval through effective sharding strategies, and the integration of Cassandra with dashboards and reporting tools. Key Responsibilities: - Design, implement, and manage scalable data models and Cassandra clusters. - Handle and process massive datasets (crores of records) with an emphasis on performance and reliability. - Optimize performance for large datasets, prioritizing speed and reliability. - Implement data sharding and partitioning strategies to facilitate distributed data storage. - Ensure fast and reliable CRUD operations on datasets with high volume. - Integrate Cassandra with visualization/dashboard tools to enable real-time data access and reporting. - Monitor, troubleshoot, and fine-tune cluster performance and availability. Required Skills: - Strong hands-on experience with Apache Cassandra in production environments. - Demonstrated ability to manage and query crores of records with high performance. - In-depth knowledge of Cassandra architecture, data modeling, and tunable consistency. - Proficiency in scripting languages such as Python/Bash, and experience in performance tuning. - Experience in integrating Cassandra with dashboarding or reporting tools. - Understanding of distributed systems and NoSQL best practices. - Familiarity with tools like Spark and Kafka. Please note that the above is a summary of the job description provided. For more information, please refer to the original source.,