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Role: Monitoring & Telemetry Engineer
Rate: Open to discussion
Location: Remote
Contract Length: 6 months with possible extensions
Description:
Monitoring & Telemetry Engineer for our algorithmic trading firm. This role is crucial for building advanced monitoring and alerting systems across thousands of Time Series Database instances and servers. Your main goal will be to proactively find and predict bottlenecks and traffic issues to keep our trading systems running smoothly.
Key Responsibilities
- Build Monitoring Systems: Design and deploy real-time monitoring and alerting for our Time Series Database trading infrastructure. Create telemetry pipelines to collect and analyze operational data.
- Predict Bottlenecks: Develop predictive models to anticipate traffic and demand, identifying potential issues before they affect trading. Set up automated early warning alerts.
- Optimize Performance: Work with teams to improve the Time Series Database queries, server settings, and overall system architecture based on monitoring insights.
- Prevent Incidents: Help reduce system outages by proactively addressing risks and performance problems. Provide data for incident analysis.
- Tooling & Automation: Select and integrate monitoring tools (e.g., Prometheus, Grafana, ELK Stack) and automate their deployment.
Required Skills & Experience (Cerebra, Telegraf)
- Monitoring & Alerting: Proven experience with large-scale monitoring solutions (e.g., Prometheus, Grafana, ELK Stack, Splunk, Datadog).
- Telemetry: Strong understanding of collecting, processing, and storing telemetry data (metrics, logs, traces).
- Time Series Database & q: Essential in-depth knowledge of Time Series Database and q programming.
- Predictive Analytics: Experience with machine learning or statistical modeling for forecasting system behavior.
- Distributed Systems: Good grasp of distributed systems and high-performance environments.
- Infrastructure: Experience monitoring systems on-premise, cloud, or hybrid.
- Scripting: Proficient in Python or Bash for automation.
- Problem-Solving: Excellent analytical and troubleshooting skills for real-time performance issues.
Desired Qualifications
- Bachelor's or Master's in Computer Science, Engineering, or a related field.
- Experience in high-frequency trading (HFT) or algo trading.
- Familiarity with network monitoring and low-latency systems.
- Experience with Docker and Kubernetes.
This is a great opportunity to impact critical trading systems. If you're a driven engineer with a passion for proactive monitoring and Time Series Database , we encourage you to apply.
