ELK Stack Engineer: Data Analytics Expert

6 days ago

Toronto, Ontario, Canada Capgemini Full time

Job Title: ELK Stack Engineer: Data Analytics Expert

About the Role:

We are seeking an experienced ELK Stack Engineer: Data Analytics Expert to join our team in Toronto, CA. As an essential member of our data analytics team, you will be responsible for designing, implementing, and maintaining the ELK stack to collect, store, process, and analyze log data from various sources.

Main Responsibilities:

  1. Design and Implement ELK Solutions: Architect and deploy solutions using Elasticsearch, Logstash, and Kibana for log management, real-time data analysis, and visualization.
  2. Maintain ELK Stack: Monitor, configure, and troubleshoot the ELK stack, ensuring optimal performance and reliability in production environments.
  3. Log Management: Configure and manage log ingestion pipelines using Logstash or Beats agents to efficiently collect and process logs and metrics.
  4. Data Analysis and Visualization: Create and maintain dashboards and visualizations in Kibana for different teams (e.g., development, security, operations) to track system performance, errors, and other metrics.
  5. Search Engine Optimization: Optimize Elasticsearch queries, mappings, and indexing to ensure efficient data storage and fast search performance.
  6. Automation: Automate the setup, configuration, and scaling of the ELK stack using tools such as Ansible, Terraform, or Kubernetes.
  7. Security and Access Control: Implement and manage security configurations in Elasticsearch, including access control, user roles, and encryption.
  8. Collaboration and Support: Collaborate with internal teams to understand their data needs and provide support in leveraging ELK stack capabilities for various use cases.
  9. Troubleshooting and Debugging: Diagnose and resolve performance issues, errors, and failures related to ELK stack components.
  10. Documentation: Maintain detailed documentation for configurations, procedures, and troubleshooting guides for internal use.

Required Skills and Qualifications:

  1. Experience with ELK Stack: Strong hands-on experience with Elasticsearch, Logstash, and Kibana.
  2. Programming and Scripting: Proficiency in scripting languages such as Python, Bash, or Groovy.
  3. Search Engine Technologies: Knowledge of Elasticsearch internals, clusters, and distributed systems.
  4. Data Processing: Experience with data collection, transformation, and parsing using Logstash or Beats.
  5. Systems Administration: Experience with Linux-based systems, networking, and system performance monitoring.
  6. Performance Optimization: Ability to optimize Elasticsearch performance for large-scale data sets, including query performance, indexing, and storage management.
  7. Cloud Platforms: Familiarity with cloud services such as AWS, Azure, or GCP is a plus.
  8. Monitoring Tools: Experience with monitoring tools like Prometheus, Grafana, or Nagios is a plus.
  9. Version Control: Proficiency with Git and other version control systems.
  10. Problem-Solving and Troubleshooting: Strong problem-solving skills, with an ability to debug and troubleshoot issues in a complex, distributed environment.
  11. Security Awareness: Understanding of security best practices related to data storage, user access, and logging.

Estimated Salary Range: $120,000 - $180,000 per annum, depending on experience.

About Capgemini: We are a global leader in consulting, technology services, and digital transformation. We help our clients transform at unprecedented rates by combining unrivaled innovation, domain expertise, and insight with a distinctive culture that empowers teams to work better together.

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