Key Responsibilities

Elasticsearch Cluster Management: Deploy, configure, and maintain Elasticsearch clusters in production environments, ensuring high availability, scalability, and performance.

Indexing and Query Optimization: Design and implement efficient indexing strategies to optimize search query performance. Work on improving Elasticsearch query performance and ensure low-latency response times.

Data Integration and ETL: Integrate various data sources (logs, databases, APIs, third party applications such as Confluence etc) into Elasticsearch. Work with data pipelines and connectors to preprocess and index data efficiently.

Troubleshooting & Performance Tuning: Identify and resolve performance bottlenecks, analyze Elasticsearch logs, and provide solutions to maintain system reliability and performance at scale.

Security and Access Control: Implement security measures such as Azure AD role-based access control (RBAC), encryption, and other techniques to ensure that data is secure and compliant with industry standards.

Monitoring & Reporting: Set up monitoring tools (Elastic Stack Monitoring, Grafana) to track cluster health, resource usage, and query performance. Provide reports and insights on system health.

Collaboration & Documentation: Collaborate with developers, data scientists, and other stakeholders to understand use cases, ensure the search infrastructure supports their needs, and provide training and documentation.

Upgrades and Patches: Plan and execute Elasticsearch version upgrades and patch management to ensure that the system remains up-to-date and secure.

Scaling and Capacity Planning: Work on horizontal and vertical scaling strategies to handle an increase in data and query load. Optimize hardware and cloud infrastructure for Elasticsearch deployments.

Requirements

Candidates must have

At least 3 years of hands on experience with Elasticsearch in a production environment, and ideally, recent experience of Elastic Enterprise Search

Proficiency in Elasticsearch setup, configuration, and cluster management.

Strong understanding of Elasticsearch APIs, indexing, and query DSL.

Experience with data ingestion and ETL tools (e.g., Logstash, Beats, Kafka).

Familiarity with Kibana for visualizing Elasticsearch data.

Experience in performance tuning and troubleshooting Elasticsearch issues.

Experience implementing security features such as authentication, authorization, and encryption in Elasticsearch.

Experience with monitoring and alerting tools like Prometheus, Grafana, Elastic Stack Monitoring, etc.

The Ideal Candidate Would Also Have

Familiarity with Azure cloud platform

Proficiency in at least one programming language (e.g., Python, Java, C#)

Experience in CI/CD Tooling, Github, Azure DevOps