About the Role:

We are seeking a skilled and experienced Datadog Developer to join one of our client's engineering team. The ideal candidate will have a strong background in observability, monitoring, and cloud-native infrastructure, with hands-on experience implementing and managing Datadog across large-scale environments.

Key Responsibilities:

Design, implement, and manage observability solutions using Datadog APM, Infrastructure Monitoring, Logs, RUM, and Dashboards. Collaborate with DevOps, SRE, and development teams to define monitoring standards and alerting strategies. Build custom Datadog dashboards and visualizations to deliver insights across services and infrastructure. Integrate Datadog with CI/CD pipelines, cloud platforms (AWS, GCP, Azure), and containerized environments (Docker, Kubernetes). Optimize Datadog configurations for performance and cost-efficiency. Troubleshoot performance bottlenecks using Datadog metrics, traces, and logs. Automate alerting, anomaly detection, and health checks for proactive monitoring. Develop documentation and runbooks for onboarding and internal team training.
 

 

Required Skills and Experience:

5+ years of experience in monitoring/observability, with at least 2–3 years of Datadog hands-on implementation. Strong understanding of cloud-native environments: AWS, GCP, or Azure. Experience with Kubernetes, Docker, and container orchestration. Familiar with Infrastructure-as-Code tools like Terraform or CloudFormation. Knowledge of CI/CD pipelines, logging tools (ELK, FluentD), and scripting (Python, Bash). Proficient in creating custom monitors, SLOs/SLIs, and Datadog dashboards. Experience with incident management and root cause analysis using observability tools.
 

 

Preferred Qualifications:

Datadog Certification(s) (e.g., Datadog Certified Monitoring Professional) Understanding of microservices architecture and distributed systems Experience in Agile/DevOps working environments