Elastic Stack Engineer

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November 15

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Urbansoft™

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Artificial Intelligence • Cybersecurity • SaaS

Urbansoft™ is a company that spearheads the digital transformation journey by developing and building mission-critical software solutions tailored to meet the specific needs of its clients. They blend human insight with cutting-edge technology to create personalized solutions in areas such as Artificial Intelligence, Blockchain, and Cybersecurity. With expertise in data engineering, web and mobile development, and robotic process automation, Urbansoft™ focuses on delivering innovative applications that enhance operational efficiencies and drive business success.

11 - 50 employees

Founded 2014

🤖 Artificial Intelligence

🔒 Cybersecurity

☁️ SaaS

📋 Description

• Lead design, implementation, monitoring and continuous improvement of Elastic-based observability and security stack. • Take ownership of detection rules, watchers, ML-models, health monitoring of data streams. • Work closely with data engineers, security operations, platform engineering, and business-units to ensure robust real-time monitoring, anomaly detection, alerting, and data integration observability. • Architect, deploy, configure and optimise the Elastic Stack (Elasticsearch, Kibana, Beats, Logstash, Elastic Machine Learning, Elastic Watcher/Alerting). • Develop and maintain JSON-based configuration files, logic and pipelines for detection rules, watchers and alerting states. • Design, build and operationalise machine-learning jobs within Elastic ML (e.g., anomaly detection, forecasting, classification) for observability/security use-cases. • Monitor, maintain and improve the health and performance of data-streams (logs, metrics, events, traces) ingesting into the Elastic cluster. • Implement and maintain alerting/notification frameworks: watchers/triggers, custom alert-logic via JSON, integration with downstream systems (Slack, Teams, PagerDuty, email, webhook). • Develop dashboards, visualisations and reports in Kibana to communicate KPIs, SLAs (data-ingestion, alert-response, model accuracy).

🎯 Requirements

• Strong hands-on experience with the Elastic Stack (Elasticsearch, Kibana, Beats, Logstash or equivalent ingestion pipelines) • Proficiency in writing and using JSON configurations and logic for detection rules, watchers, alerting frameworks, and monitoring pipelines. • Experience building and operationalising Elastic Machine Learning jobs (anomaly detection, forecasting, classifications) and interpreting model output for observability/security use-cases. • In-depth experience monitoring and maintaining the health of high-volume data streams: log/metric/event/tracing data, with attention to data latency, ingestion batching, pipeline failures, index lifecycle, and cluster resource optimisation. • Experience designing end-to-end alerting workflows (trigger logic, thresholds, multi-condition rules, escalation, notification integration). • Experience tracking and measuring integration times (data latency from source ingestion to availability in index/dashboards) and implementing improvements to reduce that latency. • Strong scripting or programming ability (e.g., Python, Bash, or similar) to automate tasks, integrations or alert-logic. • Strong analytical and problem-solving skills: ability to diagnose ingestion/pipeline/cluster issues, chain of events, root causes, and propose mitigations. • Excellent communication skills: able to articulate detection logic, ML-model results, data-latency issues and dashboards to technical and non-technical stakeholders. • Good understanding of DevOps/SRE practices (CI/CD, Infrastructure as Code, Monitoring, Logging, Alerting). • Ability to document clearly: JSON rule setups, watchers, dashboards, models, runbooks. • Bachelor’s degree in Computer Science, Information Systems or equivalent experience; or equivalent relevant industry experience.

🏖️ Benefits

• Professional development opportunities • Flexible work arrangements