Cassandra Database Admin

2 weeks ago

Pune, Maharashtra, India POWER IT SERVICES Full time ₹ 9,00,000 - ₹ 12,00,000 per year

Casandra Database Administrator

Experience: 7 years

Technical Skills:


• Strong experience with Apache Cassandra (Open Source, DataStax, Scylla DB).


• Deep understanding of Cassandra architecture, partitions, replication, and consistency levels.


• Proficiency in CQL (Cassandra Query Language) and data modelling.


• Hands-on experience with Linux (Ubuntu, RHEL, CentOS).


• Familiarity with Cassandra monitoring tools (DataStax OpsCenter, Prometheus, Grafana).


• Experience with cloud-managed Cassandra services (AWS Key spaces, Azure Cosmos DB, Google Cloud Bigtable).

Job Description:


• Install, configure, and upgrade Apache Cassandra (Open Source, DataStax, Scylla DB).


• Monitor cluster health, node status, and replication factors.


• Ensure high availability (HA) and disaster recovery strategies are in place.


• Optimize Cassandra data models, partitions, and compaction strategies.


• Tune garbage collection (GC), JVM heap settings, and read/write performance.


• Analyse slow queries using Cassandra Query Language (CQL) tracing.


• Implement authentication (LDAP, Kerberos) and role-based access control (RBAC).


• Secure Cassandra deployments with TLS/SSL encryption and firewall rules.


• Ensure compliance with GDPR, HIPAA, and PCI-DSS standards.


• Develop and manage backup and restore strategies using node tool snapshots.


• Test disaster recovery and failover strategies regularly.


• Automate Cassandra administration tasks using Bash, Python, or Ansible.


• Set up monitoring tools (Prometheus, Grafana, ELK Stack, DataStax OpsCenter).


• Implement alerting for node failures, disk usage, and read/write latency.


• Identify and resolve replication lag, tombstone accumulation, and query timeouts.


• Work with DevOps and application teams to troubleshoot performance issues.


• Maintain detailed documentation of troubleshooting procedures.


• Monitor storage, memory, and CPU usage to plan for capacity scaling.


• Optimize replication strategies for read/write scalability.


• Implement multi-datacenter replication for disaster recovery and load balancing.

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