Job Description & Details
This is a heavy-duty SRE and platform engineering gig focused squarely on keeping complex telemetry and Kubernetes systems healthy. If you enjoy digging into cluster metrics, writing automation scripts from scratch, and stabilizing large-scale migrations, this role will keep you deeply engaged.
What You'll Actually Be Doing
Your primary focus will be owning and scaling the observability and telemetry pipelines running on Kubernetes. You will spend your days writing Python automation tools to streamline monitoring, debugging containerized workloads, and ensuring that Prometheus, Grafana, and Loki are giving engineering teams clear, actionable insights into system health. It is a hands-on operational role where you will actively troubleshoot performance bottlenecks, refine CI/CD pipelines, and collaborate with developers to shore up system reliability during migrations.
The Core Tech Stack
You absolutely must know your way around Kubernetes, Python, and modern observability stacks. The team relies heavily on Prometheus and Grafana for metrics, alongside Loki or Tempo for logs and traces, so surface-level familiarity won't cut it; you need to know how to configure and troubleshoot these tools under load. Solid Linux fundamentals, Docker containerization, and Git-based workflows are non-negotiable since you'll be living in the command line and managing infrastructure-as-code daily.
Interview Expectations
Expect the interviewers to probe deeply into your incident response and troubleshooting methodology, likely asking you to walk through a scenario where a high-throughput Kubernetes cluster is dropping telemetry data or throwing mysterious OOM kills. They are secretly testing whether you can stay calm under pressure, trace a failure systematically from the application logs up to the infrastructure layer, and write a quick Python script to prevent it from happening again.
Application Advice
To get past the ATS for this W2 role, ensure your resume explicitly highlights your hands-on experience with Prometheus, Grafana, and writing Python automation scripts specifically within Kubernetes environments. Don't just list tools; detail how you used them to improve system observability, reduce MTTR, or streamline migrations. Make sure 'DevOps', 'SRE', 'Kubernetes', and 'Python' appear naturally in your recent project descriptions to match the core weighting of the job requirements.