Muhammed Rabih

Experienced for 4 years as ELK and Data Engineer with hands-on expertise in building scalable data infrastructure and real-time monitoring systems. Proficient in the ELK Stack (Elasticsearch, Logstash, Kibana), Beats, Prometheus, and Kafka, Etc., with strong capabilities in designing and implementing robust data pipelines. Adept at transforming raw data into actionable insights, developing custom dashboards, and integrating systems for high availability and performance.

Skilled in Python, Docker, and cloud platforms like Microsoft Azure. Proven ability to collaborate across teams, ensure data accuracy, and drive solutions that support business intelligence and analytics goals.

• Designed and implemented on-premises, end-to-end ELK Stack solutions (Elasticsearch, Logstash, Kibana) with high-availability clusters, optimized shard allocation, replication strategies, and index lifecycle management (ILM) for centralized logging, monitoring, and analytics. 
• Configured index templates, mappings, and analyzers to ensure efficient data modeling, optimized indexing, and fast retrieval for large-scale datasets. 
• Built scalable Logstash pipelines and deployed Filebeat/Metricbeat to collect diverse data sources including logs, metrics, SIP call data, SNMP traps, APIs, HTTP, TCP/UDP, and biometric/RFID devices. 
• Developed custom Grok filters and enrichment logic to normalize raw data and append metadata (device type, IP, status, site, region, severity) for enhanced search and reporting. 
• Troubleshot and resolved Elasticsearch cluster issues related to performance, health, data integrity, and availability, ensuring minimal downtime and reliable search operations. 
• Optimized DSL queries and bulk ingestion processes, reducing search latency and improving throughput. 
• Created interactive Kibana dashboards for real-time monitoring of system health, device utilization, attendance, and business KPIs. 
• Implemented real-time alerting and anomaly detection (e.g., SIP errors, latency spikes, device failures) leveraging Elasticsearch rules and Watcher. 
• Designed and modified index lifecycle policies, state management strategies, and ingest pipelines for long-term data storage and security analytics use cases. 
• Deployed and configured Prometheus with exporters, integrating metrics into Grafana dashboards for unified observability with ELK. 
• Integrated Kafka for real-time data streaming and Docker for containerized deployments, ensuring scalability and portability. 
• Collaborated across DevOps, QA, and business teams to deliver end-to-end observability solutions, incorporating CI/CD workflows, authentication, and security compliance. 
• Hands-on expertise in Linux-based deployments, Git/GitLab, and Jira for agile project execution and environment management. 

B.E Mechanical Engineering