Senior Elasticsearch Engineer
Leidos has an exciting opening for you as our next TS/SCI cleared Senior Elasticsearch Engineer supporting DIA-NMEC under our 10-year DOMEX Technology Platform (DTP) contract. We are seeking a highly skilled and experienced Senior Elasticsearch Engineer to join our dynamic team. As a Senior Elasticsearch Engineer, you will play a pivotal role in designing, implementing, and optimizing our Elasticsearch infrastructure to support our growing data and search needs. You will collaborate with cross-functional teams to ensure the reliability, performance, and scalability of our Elasticsearch clusters. While most work is conducted on-site at our client location in Bethesda, MD, we offer a flexible schedule and, occasionally, some tasks may be performed remotely. Percentage of remote work will vary based on client requirements/deliverables.
As an integral member of the team, you will work closely with other infrastructure, network engineers, and system engineers on the following key tasks:
- Design, implement, and manage Elasticsearch clusters to support large-scale data indexing and search operations.
- Optimize Elasticsearch performance by fine-tuning configurations, query optimizations, and cluster scaling.
- Monitor Elasticsearch clusters for health, performance, and security, and implement proactive measures to ensure system stability.
- Collaborate with software development and DevOps teams to integrate Elasticsearch into our applications and workflows.
- Troubleshoot and resolve complex Elasticsearch-related issues, ensuring minimal downtime and data loss.
- Implement security best practices for Elasticsearch, including access controls, authentication, and encryption.
- Stay up-to-date with Elasticsearch and ELK Stack (Elasticsearch, Logstash, Kibana) developments and recommend upgrades or enhancements.
- Mentor and provide guidance to junior team members, sharing knowledge and best practices.
- Document configurations, procedures, and best practices for Elasticsearch administration.
You demonstrate clear devotion to the DevOps and Infrastructure as Code (IaC) mindset and meet the following qualifications:
- Bachelor’s Degree and 8+ years of proven experience as an Elasticsearch Engineer or Master’s with 1-2 years of proven experience as an Elasticsearch Engineer
- Must possess an Active Top Secret clearance and ability to obtain TS/SCI with CI Poly
- Experience in system integrations testing through a full system development life cycle, including implementing test plans, test cases and test processes.
- Strong expertise in Elasticsearch cluster design, performance tuning, and optimization
- Proficiency in Elasticsearch query DSL and search query optimization.
- Experience with Logstash, Kibana, Metricbeats, and Filebeats is a plus.
- Knowledge of Elasticsearch security practices, including role-based access control and SSL/TLS.
- Scripting and automation skills with tools like Python, Bash, or Ansible.
- Familiarity with cloud platforms like AWS.
- Working in an Agile project management environment
- Experience documenting test results for corrective actions, reporting and audits
- Strong verbal and written communication skills
- Enthusiastic with the ability to work well on a team and a self-starter who can work on their own
You will wow us even more if you have some of these:
- Knowledge of Atlassian software such as JIRA, JIRA Service Desk, and Confluence
- Experience with data engineering tools such as Kubernetes/Rancher, Cloudera
- Experience with scripting languages, CI/CD tools, like Jenkins or Gitlab
- Experience working in an air-gapped environments
- Experience working in large computing environments (> 1,000 end-points)
- Experience maintaining AI/ML environments (NVIDIA hardware and software)
- Experience maintaining large data (Petabyte) environments and storage solutions
- Experience with advanced Linux network hardware (eg: Mellanox Network Cards)
Pay Range:Pay Range $84,500.00 - $152,750.00
The Leidos pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.