Sr.ElasticsearchEngineer

Sr. Elasticsearch Engineer
Location: Open to 100% remote candidates working mostly 9-5 MST schedule
Duration: 12+ Months Contract (Potential to extend)

Requirements:

• MUST HAVE
• 5+ years' experience designing and managing production ready multi-cluster Elasticsearch instances in AWS public cloud
• Unix/Linux experience managing and implementing and troubleshooting it
• Great understanding of how search works across different platforms is fine, but knows in terms of indexes, every component that supports ecosystem like Kafka which they use. (Could be RabbitMQ, AMQ experience)
• Soft skills:
• Excellent communication and collaboration skills, with the ability to work ask for help from team members and proactively find additional work
• Willing to speak up and share best practices from their own past experiences to help team avoid pitfalls
• NICE TO HAVE
• Using Elastic as a Document management platform strongly preferred
• Python for scripting/automation, using PowerShell in current environment now but that will shift to Python over time
• TerraForm they are building it out as Infrastructure as Code

Job Description:

Responsibilities

• Design, implement and manage scalable Elasticsearch clusters optimized for indexing and querying large volumes of documents
• Drive architectural reviews and provide technical guidance on complex search implementations.
• Administer the operations of multiple production Elasticsearch clusters across different environments.
• Drive observability and monitoring for Elasticsearch clusters.
• Implement robust ingest pipelines for structured and unstructured file types.
• Develop and fine-tune full-text search features for relevance, speed, and accuracy
• Integrate file parsing tools (e.g., Apache Tika, ingest-attachment plugin) into indexing workflows.
• Conduct regular security audits and vulnerability assessments.
• Provide technical support to internal and external staff.
• Participate in incident calls and problem resolution.
• Architect index structures, lifecycle management, and document storage patterns
• Ensure secure access to document content through fine-grained RBAC and SSO integration
• Build metadata extraction and enrichment services to augment searchability
• Automate ingestion pipelines using scripting (Python, Bash, PowerShell)
• Develop dashboards for search/reporting use cases in collaboration with product teams
• Collaborate with Engineering to optimize search integration and performance.
• Deploy and manage Kafka instances.
• Cluster tuning and scaling with focus on fast search and analytics at scale.
• Carry out capacity planning and migrations to optimize cluster performance.