Offer summary

Qualifications:

Proven experience with Infrastructure-as-Code tools like Terraform., Strong understanding of DevOps and Service Level Management metrics., Experience with monitoring and observability tools such as New Relic and Grafana., Familiarity with cloud infrastructure management on AWS, Azure, or GCP..

Key responsabilities:

Design and maintain scalable and highly available systems using load balancing and auto-scaling patterns.

Develop monitoring and logging dashboards to ensure observability of systems.

Collaborate with cross-functional teams to enhance platform engineering practices.

Implement Chaos engineering practices to ensure system resiliency.

Job description

This is a remote position.

We are seeking a highly skilled Senior Site Reliability Engineer (SRE) to join our Platform Engineering team. The ideal candidate will have a strong understanding of DevOps and Service Level Management (SLM) metrics. As well as experience working in event-driven infrastructure projects using tools like Terraform, New Relic, Kubernetes, AWS, and Kafka.

As a representative of Platform Engineering, you will play a critical role working with other engineering teams to ensure our platform infrastructure tooling fulfils their needs and has a positive impact on Developer Experience. As well as helping them determine the right settings and thresholds for triggering alerts or automations on their applications.

Key Responsibilities:

Scalability and High Availability: Design, implement, and maintain scalable and highly available systems using load balancing, auto-scaling patterns, canary releases, and blue-green deployments.
Monitoring, Logging, and Observability: Develop and maintain monitoring and logging dashboards using tools like New Relic, Prometheus, Grafana, and Datadog.
Ensure observability through metrics, tracing, log aggregation, and alerting.
Alerting and Automation: Help teams determine the right settings and thresholds for triggering alerts or automations on their applications.
Understand that each application has different performance requirements, such as varying acceptable response times or resource constraints.
System Performance and Reliability: Monitor, optimize, and ensure system reliability and performance using tools like New Relic.
Apply DORA metrics to measure and improve development and operational performance.
Ensure compliance with SLM metrics like SLAs, SLOs, and SLIs by tracking uptime, response times, and resolution times.
Resiliency: Implement and advocate for "Chaos" engineering practices to ensure system resiliency.
Collaboration: Work with cross-functional teams to enhance platform engineering practices and gathering the right information for metrics analysis.

Requirements

Proven experience working with Infrastructure-as-Code tooling, like Terraform, for infrastructure management.
Strong understanding of scalability and high availability patterns, including load balancing, auto-scaling, canary releases, and blue-green deployments.
Strong understanding of DevOps metrics (like DORA) and their application in measuring and improving development and operational performance.
Strong understanding of Service Level Management (SLM) metrics (like SLAs, SLOs, and SLIs). And their importance in defining, monitoring, and ensuring compliance from the services bound to them.
Experience with monitoring, logging, and observability tools like New Relic, Prometheus, Grafana, and Datadog.
Experience working with Kafka and improving performance of event-driven, realtime data processing and streaming projects and architectures.
Familiarity with tooling used for SLM, DevOps and DORA metrics like Apache Dev Lake, Grafana and New Relic.
Experience working with AWS, Azure or GCP for cloud infrastructure management.
Experience working with CI/CD pipeline tools such as GitHub Actions, Jenkins, GitLab CI, or similar.
Analytical Skills. Ability to analyze and interpret metrics to drive improvements.
Strong communication skills to effectively collaborate with team members and stakeholders.
Nice-to-haves Familiarity with Observability-as-Code tooling and practices.
Familiarity with "Chaos" engineering practices for system resiliency