What are the responsibilities and job description for the Sr. Platform Engineer (Elasticseacrh) position at Optomi?
Senior Platform Engineer (Elasticsearch) | Hybrid in Baltimore & Evansville | Contract
Optomi, in partnership with a leading finance organization, is seeking an experienced Senior Platform Engineer to join their team! This role is perfect for a hands-on engineer who will own the end-to-end lifecycle of an enterprise-grade Elasticsearch platform, driving design, deployment, optimization, and automation for large-scale search, observability, and log analytics solutions.
Experience of the right candidate:
- 3–5 years of hands-on experience Elasticsearch administration in enterprise environments
- Proven track record designing and deploying ELK/Elastic Stack at scale
- Expert in Elasticsearch architecture: nodes, shards, replicas, indexing, search, aggregations, APIs
- Proficiency in scripting/automation: Python, Bash, Ansible; Go or Java a plus
- Experience with cloud platforms (AWS, Azure, GCP) and container orchestration (Kubernetes, Docker)
- Solid grasp of distributed systems, networking, and storage (EBS, GP3, etc.)
- Experience with automation and scripting (Python, Bash, Terraform, Ansible, or similar)
- Deep knowledge of system performance tuning, incident management, and root cause analysis
- Familiarity with CI/CD pipelines (GitHub,Gitlab) and DevOps best practices
- Excellent problem-solving and communication skills.
Responsibilities of the right candidate:
- Architect and deploy scalable Elasticsearch solutions for search, observability, and logs/metrics analytics’ use cases.
- Design and implement ELK/Elastic Stack (Elasticsearch, Logstash, Kibana) and complementary pipelines.
- Create and manage multi-node clusters across availability zones in cloud and/or on-prem environments.
- Monitor, maintain, and troubleshoot ELK/Elastic environments & Elasticsearch clusters for performance, stability, and data integrity.
- Perform performance tuning namely query optimization, indexing pipelines and shard rebalancing.
- Conduct capacity planning, configuration management, and continuous improvement via metrics, alerts, and automation.
- Execute version upgrades, patching, and backward-compatible migrations with minimal downtime.
- Build and maintain Infrastructure as Code (Terraform/Ansible), CI/CD pipelines, and automation scripts (Python, Bash, etc...).
- Integrate Elasticsearch with cloud providers, cloud-native services, and other opensource observability tools.
- Enable self-service capabilities for development teams via APIs, templates, and dashboards
- Provide expert guidance, code/config reviews, and lightweight scripting to accelerate feature delivery.
- Create and maintain runbooks, architecture diagrams, KPIs dashboards (Kibana), and troubleshooting guides.
- Evaluate and adopt new Elastic features, plugins, and ecosystem tools.
- Lead proof-of-concepts for advanced use cases (machine learning, cross-cluster replication etc…).
- Identify automation opportunities and drive platform resilience initiatives.