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Datadog Jobs in Arizona (NOW HIRING)

Datadog o similares). * Conocimiento en: * Arquitecturas de microservicios * APIs REST * Sistemas distribuidos * Experiencia en observabilidad: * Metrics, logs y traces * Manejo de entornos cloud ...

$52.50 - $68.25/hr

Monitor Kafka clusters and pipelines using tools such as Confluent Control Center, Prometheus, Grafana, or Datadog to track consumer lag and key performance metrics. * Collaborate with architects and ...

.Net Developer

Tempe, AZ

$47 - $62/hr

Log monitoring (DataDog, Application insights, etc..) * Automation (Playwright, xUnit, etc..) At a highest level, our API services look like this Client Graphql ( Federated Gateway (typescript ...

.Net Developer

Tempe, AZ · On-site

$47 - $62/hr

Log monitoring (DataDog, Application insights, etc..) * Automation (Playwright, xUnit, etc..) At a highest level, our API services look like this Client à Graphql ( Federated Gateway (typescript) à ...

Integrate observability tools (CloudWatch, Datadog, Splunk, OpenTelemetry) for network monitoring and alerting. Optimize network performance, cost, and security. Lead incident triage, root cause ...

... Datadog, Splunk, OpenTelemetry) for network monitoring and alerting. • Optimize network performance, cost, and security. • Lead incident triage, root cause analysis, and postmortems. • ...

... Datadog, Splunk, OpenTelemetry) for network monitoring and alerting. • Optimize network performance, cost, and security. • Lead incident triage, root cause analysis, and postmortems. • ...

Debug and resolve production issues using AWS CloudWatch logs, Datadog, and other monitoring tools * Conduct code reviews and mentor junior developers, promoting coding best practices and quality ...

Developer, Back End

Tempe, AZ · On-site

$114K - $135K/yr

Debug and resolve production issues using AWS CloudWatch logs, Datadog, and other monitoring tools * Conduct code reviews and mentor junior developers, promoting coding best practices and quality ...

Build and manage monitoring platforms such as Datadog, Grafana, Prometheus, and AWS CloudWatch -- actively exploring AI-native features within these tools to reduce alert fatigue and improve signal ...

Debug and resolve production issues using AWS CloudWatch logs, Datadog, and other monitoring tools * Conduct code reviews and mentor junior developers, promoting coding best practices and quality ...

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Showing results 1-20

Datadog information

What is the difference between Datadog vs Cloud Monitoring Engineer?

AspectDatadogCloud Monitoring Engineer
Primary RoleMonitoring and analytics platform for IT infrastructure and applicationsDesigning, implementing, and managing cloud monitoring solutions
Required SkillsCloud platforms, monitoring tools, scripting, API integrationCloud services, monitoring tools, scripting, troubleshooting
CertificationsCloud certifications (AWS, Azure), monitoring tools certificationsCloud certifications (AWS, Azure), monitoring certifications
Work EnvironmentUsing SaaS platform, integrating with various cloud and on-premise systemsManaging cloud infrastructure, configuring monitoring tools, troubleshooting

While both roles involve cloud monitoring, Datadog focuses on utilizing a specific SaaS platform for analytics and monitoring, whereas a Cloud Monitoring Engineer designs and manages monitoring solutions across cloud environments. The roles often overlap in skills and certifications, but their core responsibilities differ in scope and focus.

What are the key skills and qualifications needed to thrive as a Datadog Engineer, and why are they important?

To thrive as a Datadog Engineer, you need a solid understanding of cloud infrastructure, monitoring and observability principles, and experience with scripting or programming languages. Familiarity with Datadog’s platform, API integrations, and certifications such as Datadog Certified Technical Specialist are highly valuable. Strong problem-solving skills, attention to detail, and effective communication help you proactively address system issues and collaborate with cross-functional teams. These skills ensure efficient system monitoring, rapid incident response, and reliable service performance in dynamic technology environments.

What are some common challenges faced by Datadog engineers when implementing monitoring solutions for large-scale systems?

Datadog engineers often encounter challenges such as integrating diverse technology stacks, ensuring minimal performance impact, and maintaining data accuracy across high-traffic environments. Large-scale systems can generate vast amounts of telemetry data, so configuring efficient dashboards and alerting without causing alert fatigue is vital. Collaborating closely with development, operations, and security teams is essential to tailor monitoring solutions that provide actionable insights while staying adaptable to evolving system architectures.

What is a Datadog engineer?

A Datadog engineer is a professional who specializes in implementing, configuring, and managing Datadog, a cloud-based monitoring and analytics platform. They are responsible for integrating Datadog with various systems, setting up dashboards, alerts, and metrics to monitor application performance and infrastructure health. Their work helps organizations identify issues, optimize performance, and ensure system reliability. Datadog engineers often collaborate with DevOps, IT, and development teams to provide insights and improve observability across environments.
What cities in Arizona are hiring for Datadog jobs? Cities in Arizona with the most Datadog job openings:

Full-time

Posted 13 days ago


Job description

Buscamos un/a consultor/a especialista en monitoreo de aplicaciones con foco en performance, observabilidad y troubleshooting avanzado, para acompañar la implementación, optimización y operación de plataformas APM como Datadog, New Relic, Dynatrace.

Responsabilidades principales:
  • Implementar y configurar soluciones APM end-to-end (instrumentación, agentes, dashboards).

  • Trabajar sobre trazas (tracing distribuido) y logs correlacionados.

  • Participar en análisis de incidentes críticos (root cause analysis).

  • Optimizar la observabilidad en entornos cloud y microservicios.

  • Generar documentación técnica y buenas prácticas.

  • Interactuar con equipos de desarrollo, infraestructura y seguridad.

Requisitos técnicos:
  • Experiencia comprobable en herramientas APM (ideal: Datadog o similares).

  • Conocimiento en:

    • Arquitecturas de microservicios

    • APIs REST

    • Sistemas distribuidos

  • Experiencia en observabilidad:

    • Metrics, logs y traces

  • Manejo de entornos cloud (AWS, Azure o GCP).

  • Experiencia en troubleshooting de performance.

  • Conocimientos básicos de networking (latencia, DNS, etc.).

  • Scripting (Python, Bash o similar).

  • Conocimiento en OpenTelemetry. 

(PLUS - proyectos reales de implementación)