Technical Specialist - GraphDB

As a Technical Support Engineer at our company, you will play a crucial role in providing high-quality technical support to our global client base and partners. Your primary responsibility will involve troubleshooting complex technical issues related to our Data based Software Product, ensuring product adoption, and ultimately driving customer satisfaction. **Roles and Responsibilities:** - Respond to customer inquiries and deliver in-depth technical support through various communication channels. - Collaborate with core engineering and solution engineering teams to diagnose and resolve intricate technical problems. - Create and maintain public documentation, internal knowledge base articles, and FAQs to support customer needs. - Monitor and meet SLAs to ensure timely resolution of technical issues. - Efficiently triage varying issues based on error messages, log files, threads dumps, stack traces, sample code, and other available data points. - Troubleshoot cluster issues across multiple servers, data centers, and regions in various cloud environments. - Work during EMEA time zone (2PM to 10 PM shift) to cater to customer needs effectively. **Requirements:** **Must Have Skills:** - **Education:** B.Tech in computer engineering, Information Technology, or related field. - **Experience:** - GraphDB experience is a must. - 5+ years of experience in a Technical Support Role on Data based Software Product at least L3 level. - Linux Expertise: 4+ years with a deep understanding of Linux, including filesystem, process management, memory management, networking, and security. - Graph Databases: 3+ years of experience with Neo4j or similar graph database systems. - SQL Expertise: 3+ years of experience in SQL for database querying, performance tuning, and debugging. - Data Streaming & Processing: 2+ years hands-on experience with Kafka, Zookeeper, and Spark. - Scripting & Automation: 2+ years with strong skills in Bash scripting and Python for automation, task management, and issue resolution. - Containerization & Orchestration: 1+ year proficiency in Docker, Kubernetes, or other containerization technologies is essential. - Monitoring & Performance Tools: Experience with Grafana, Datadog, Prometheus, or similar tools for system and performance monitoring. - Networking & Load Balancing: Proficient in TCP/IP, load balancing strategies, and troubleshooting network-related issues. - Web & API Technologies: Understanding of HTTP, SSL, REST APIs for debugging and troubleshooting API-related issues. **Nice to have Skills:** - Familiarity with Data Science or ML will be an edge. - Experience with LDAP, SSO, OAuth authentication. - Strong understanding of database internals and system architecture. - Cloud certification (at least DevOps Engineer level),