SRE Operations Engineer

L1 SRE Operations Engineer in Dallas, TX. Start date is 5/11 and will last for 1 YEAR. This is a temp to perm role

can be based in Dallas TX or Overland Park, KS

Pay Rate is 52.00-58.00/hr

Skills (EXPERT/ADVANCED/NONE): 
System & Infrastructure Monitoring
Runbook Execution
Incident Triage & Communication
Kubernetes (Cloud or onprem) operations knowledge
Scripting (Python, Bash, PowerShell)
Networking & Security Awareness
Documentation & Knowledge Capture

Questions (must reply YES to ALL):
Do you have System & Infrastructure Monitoring experience?
Do you have Runbook Execution experience?
 
Description:
SRE Operations Engineer

The L1 SRE is the first line of defense in monitoring, triaging, and executing standardized operational tasks for all enterprise applications running on standard patterns and platforms like Kubernetes, APIs, WAF, databases, API Proxy (Gloo, APIGEE), Kafka, and Cloud (AWS/Azure/Google Cloud Platform). They will followrunbooks, leverage automation, and escalate appropriately to minimize downtime.

Skills
Mandatory Skills (Must-Have)
1. System & Infrastructure Monitoring
Expectation: Ability to use monitoring dashboards (e.g., Grafana, Datadog, Splunk, Argos, AIOps) toidentify anomalies, follow alert workflows, and escalate when thresholds are breached.
Example: When a Kubernetes pod crash-loop is flagged in Prometheus, L1 should validate it againstrunbooks, check pod logs, and escalate if restart attempts fail.
2. Runbook Execution
Expectation: Strictly follow documented steps to resolve standard incidents, escalate when stepsdo not apply or fail.
Example: Use a provided runbook to restart a failed API proxy service; if error persists beyonddocumented steps, escalate to L2.
3. Incident Triage & Communication
Expectation: Perform first-line triage of alerts, gather logs/metrics, categorize severity, and notifystakeholders in clear, concise language.
Example: For a database connection timeout, collect error logs, verify service reachability, andprovide a detailed incident note to L2 before escalation.
4. Kubernetes (Cloud or onprem) operations knowledge
Expectation: Ability to check pod status, understand logs, and verify service endpoints usingkubectl and monitoring tools.
Example: Run kubectl get pods -n to verify if deployments arehealthy.
5. Scripting (Python, Bash, PowerShell)
Expectation: Able to read and make small edits to scripts to automate repetitive checks.
Example: Modify a Bash script to include an additional log path in a health check.
6. Networking & Security Awareness
Expectation: Understand troubleshooting (ping, netstat, curl, traceroute) and know when issuesmay be related to firewall, WAF, or proxy.
Example: For an unreachable service, confirm DNS resolution and connectivity before escalating toL2.
7. Documentation & Knowledge Capture
Expectation: Accurately record steps taken during incidents, suggest runbook updates where gapsexist.
Example: After handling an alert for disk usage, note missing cleanup steps in the runbook and flagfor update.

Preferred Skills (Nice-to-Have)
1. Cloud Platform Familiarity (AWS, Azure, Google Cloud Platform)
Expectation: Understand basics of cloud services (VMs, load balancers, storage) and how tonavigate a cloud console.
Example: Use AWS Console to check EC2 instance health status when a service alert is triggered.
2.Database Basics (SQL/NoSQL)
Expectation: Run simple queries to validate DB connectivity and health.
Example: Execute
SELECT 1; to verify a database is reachable.
3. Automation & Self-Service Mindset
Expectation: Identify repetitive manual steps and propose candidates for automation.
Example: Flag that manual log collection during outages could be replaced with a script.
4. Exposure to Incident Management Tools (xMatters, ServiceNow, Jira, etc.)
Expectation: Comfortable working within ITSM/incident workflows.
Example: Log incident details in ServiceNow with accurate categorization and timestamps.
5. AI/Chatbot-Assisted Ops (emerging skill)
Expectation: Use AI assistants to search runbooks or suggest remediation steps.
Example: Ask an AI ops assistant to summarize logs before escalation.

Qualifications
2–5 years in IT operations, NOC, or SRE/DevOps engineer role.
Kubernetes 101, Linux 101, Networking 101
Understanding of cloud-ready applications
Understanding of observability tools (Prometheus, Grafana, ELK, Splunk, etc.).
Strong troubleshooting mindset, ability to follow structured workflows. Eg: 5 Why?s and Fishbone