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Engineer II

4 months ago

Pune, India Parallel Wireless Full time
People come to work at Parallel Wireless because we are building the future of telecom. They stay, because they are challenged and driven by an incredible product and team. We take pride in our commitment to employee development, and our culture fosters an atmosphere of empowerment, trust, respect, and communication. . What you will do : 1. Set up, configure, and optimize Elasticsearch architecture for performance and scalability.2. Develop scripts and automation tools (Python, Bash) for efficient management and configuration of Elasticsearch. 3. Implement and enforce security best practices for Elasticsearch clusters. 4. Utilize Elasticsearch Query DSL and mapping to optimize search performance and data indexing. 5. Design and create advanced visualizations and dashboards in Kibana to provide insights into data. 6. Establish monitoring and alerting systems in the ELK stack to ensure system health and performance. 7. Employ Logstash Grok patterns and other filters to seamlessly integrate logs from third-party applications. 8. Configure and optimize APM (Application Performance Monitoring) setups. 9. Integrate Mainframe/Corebanking logs into ELK for comprehensive log management and analysis. 10. Design logging frameworks for applications to ensure consistent and structured logging practices. 11. Collaborate with data scientists to implement machine learning workflows in ELK for data analysis and anomaly detection.

What you need :

Bachelor’s degree in computer science engineering, or related field. 5+ years of experience as an Elastic Engineer or similar role. Proficiency in Elasticsearch architecture, configuration, and performance tuning. Strong scripting and automation skills with Python, Bash, or similar languages. In-depth understanding of security best practices for Elasticsearch clusters. Experience with Elasticsearch Query DSL and mapping. Demonstrated ability to create advanced visualizations and dashboards in Kibana. Familiarity with setting up monitoring and alerting systems in the ELK stack. Experience in Logstash Grok patterns and other filters for log integration. Knowledge of APM setup and configurations. Experience integrating Mainframe/Corebanking logs into ELK is a plus. Ability to design logging frameworks for applications. Understanding of machine learning workflows in ELK is advantageous.