Elastic Database Solutions Expert

3 days ago


San Antonio, Texas, United States ITI Solutions Full time
Elastic Database Engineer

The Elastic Database Engineer will provide expertise in the implementation, management, and maintenance of Elastic Stack solutions within the 367th Cyberspace Operations Squadron (COS). This role requires a deep understanding of Elasticsearch, Logstash, Kibana, and related tools.

Key Responsibilities:
  • Provide Subject Matter Expertise for ELK software.
  • Demonstrate knowledge of different Elasticsearch versions and data migration techniques.
  • Install, configure, troubleshoot, and patch Elastic Stack software.
  • Demonstrate working knowledge of host computing, virtual machine computing, and ELK software operation in Docker, Kubernetes, and cloud environments.
  • Ingest data into Elastic Stack and transform it for advanced analysis.
  • Demonstrate knowledge of programming languages common to ELK (Painless, Ruby, Query DSL).
Requirements:
  • Strong understanding of Elastic Stack architecture and functionalities.
  • Expertise in data manipulation, transformation, and analysis.
  • Proficiency in Python programming and scripting.
  • Familiarity with REST APIs, JSON data format, and data interchange.
  • Ability to develop, troubleshoot, and maintain custom scripts for data automation.
  • Excellent communication and collaboration skills.
  • Ability to provide On-the-Job Training (OJT) to others.
  • Ability to obtain and maintain the required security clearance.
  • Willingness to maintain CompTIA Security+ certification.
Education and Certifications:
  • Bachelor's degree in Computer Science, Information Technology, or a related field is preferred.
  • CompTIA Security+ certification (DoD 8570 IAT Level II compliant) is required.
Relevant Experience:
  • At least 3 years of experience with Elastic Stack software (Elasticsearch, Logstash, Kibana, Beats).
  • Demonstrated experience with data ingestion, data transformation, and data analysis using Elastic Stack.
  • Experience with Python programming for data analysis and machine learning.
  • Familiarity with Docker, Kubernetes, and cloud environments.
  • Knowledge of Data Science principles, data enhancement, and data analysis techniques.


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