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Datadog Jobs in Raleigh, NC (NOW HIRING)

1 point system

Sr. Java Developer

Durham, NC · On-site

$55.25 - $70.50/hr

AppDynamics/Dynatrace/Datadog ; logs via Splunk or ELK/OpenSearch. * Testing discipline: TDD with JUnit 5, Mockito; strong coverage habits. * Infrastructure as Code: Terraform/CloudFormation.

Compunnel

Systems Analyst

Durham, NC · On-site

... as Datadog and Splunk. • Excellent analytical, problem-solving, communication, and presentation skills. • Ability to collaborate effectively with business, architecture, engineering, and ...

1 point system

Sr. Java Developer

Durham, NC · On-site

$50 - $52/hr

AppDynamics/Dynatrace/Datadog ; logs via Splunk or ELK/OpenSearch. * Testing discipline: TDD with JUnit 5, Mockito; strong coverage habits. * Infrastructure as Code: Terraform/CloudFormation.

DPR Construction

MLOps Engineer

Raleigh, NC

Experiencestanding up and managingobservability tools such as Datadog, Azure Monitor or GrafanaforAPM, LLM Opsand model performance monitoring * Experiencedeploying production-ready machine learning ...

Fidelity Investments

Director, Architecture

Durham, NC · Hybrid

$244K/yr

Analyzes production and performance issues with mobile applications using Splunk and Datadog to identify and troubleshoot issues. Builds secure, password-less, and biometric authentication features ...

Fidelity Investments

Principal Cloud Engineer

Durham, NC · On-site

$53.75 - $72/hr

Leverages CloudFormation, YML, Vault, Bitbucket, Artifactory, CloudWatch, and DataDog to determine performance metrics, event monitoring for infrastructure and cloud services, enable automated ...

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All JobsDatadog JobsDatadog Jobs in Raleigh, NC

Datadog information

See Raleigh, NC salary details

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How much do datadog jobs pay per hour?

As of Aug 8, 2026, the average hourly pay for datadog in Raleigh, NC is $20.52, according to ZipRecruiter salary data. Most workers in this role earn between $16.83 and $20.58 per hour, depending on experience, location, and employer.

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?

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 are popular job titles related to Datadog jobs in Raleigh, NC? For Datadog jobs in Raleigh, NC, the most frequently searched job titles are:
What job categories do people searching Datadog jobs in Raleigh, NC look for? The top searched job categories for Datadog jobs in Raleigh, NC are:
What cities near Raleigh, NC are hiring for Datadog jobs? Cities near Raleigh, NC with the most Datadog job openings:
Datadog jobs near you
Infographic showing various Datadog job openings in Raleigh, NC as of July 2026, with employment types broken down into 89% Full Time, 4% Part Time, and 7% Contract. Highlights an 76% Physical, 6% Hybrid, and 18% Remote job distribution, with an average salary of $42,678 per year, or $20.5 per hour.

Sr. Java Developer

1 point system

Durham, NC • On-site

$55.25 - $70.50/hr

Contractor

Posted 17 days ago

Job description

MUST HAVE:

  • 6-7 years as a Java Developer  java 11-21 & Spring Boot
  • Strong AWS experience (hands-on preferred)
  • Messaging systems experience (Kafka, RabbitMQ, or SQS)
  • Experience building and maintaining backend services in a production environment

Nice To Have:

  • Exposure to Infrastructure as Code (Terraform – nice to have)
  •  Familiarity with AI coding tools (Claude, Cursor, Codex) – highly valued

Job Description:

Team: Histology Pod – Connect Program (Corporate IT)

About the Program

  • The Connect program is a multi‑year modernization initiative migrating legacy COBOL-based LIMS systems to a modern Java + Spring Boot + Angular + AWS stack. The system spans 35 medical disciplines, with Histology and Cytology as key modules. This role joins the Histology pod, supporting both a backfill and new feature expansion as additional lab workflows come online.
  • You’ll build in a brownfield environment: extending and evolving a complex, high-dependency system where disciplined sequencing and architecture choices matter.

What You’ll Do

  • Design, build, and deploy RESTful microservices with Spring Boot on AWS, following enterprise standards and secure-by-default practices.
  • Collaborate directly with business stakeholders via the liaison team to understand lab workflows and translate them into scalable, reliable services.
  • Promote engineering excellence: code quality, testing discipline, observability, secure coding, and CI/CD best practices.
  • Mentor engineers on design choices, code reviews, and modern Java practices.
  • Champion AI-augmented development (e.g., Cursor, CodeWhisperer, Cloud Code) to improve productivity and delivery speed.
  • Participate in Agile ceremonies (daily standups, sprint planning/reviews) and contribute to continuous improvement.

Must-Have Qualifications

  • 6+ years backend engineering experience building enterprise-grade systems.
  • Strong Java (11–21) fundamentals; modern Java features and idioms preferred.
  • Spring Boot and REST API development experience (required).
  • AWS (critical must-have): 3+ years hands-on experience (prefer 5+) with services such as Lambda, S3, SQS/SNS, API Gateway, ECS/EKS/EC2, IAM. AWS depth matters more than generic “cloud.”
  • Brownfield systems experience: evolving existing platforms, respecting constraints, and sequencing changes to avoid system-level dependency conflicts.
  • Solid understanding of application security (e.g., Spring Security, OAuth 2.0, OIDC) and secure design.
  • Proficiency with datastores: SQL (e.g., Postgres/Oracle) and at least familiarity with NoSQL (e.g., DynamoDB).
  • CI/CD with Git-based workflows and build tools (Jenkins/GitHub Actions, Maven/Gradle, SonarQube).
  • Strong communication skills and the ability to work directly with business stakeholders on requirements and workflows.
  • Openness to AI tooling in day-to-day development; able to discuss what you’ve tried and how you use it responsibly and effectively.

Nice-to-Have

  • Messaging/eventing: Kafka, RabbitMQ, SQS/SNS (used in the environment; not a deal-breaker).
  • Containerization & platforms: Docker, Kubernetes/OpenShift.
  • Observability: AppDynamics/Dynatrace/Datadog; logs via Splunk or ELK/OpenSearch.
  • Testing discipline: TDD with JUnit 5, Mockito; strong coverage habits.
  • Infrastructure as Code: Terraform/CloudFormation.
  • Experience in healthcare/LIMS domain.
  • Familiarity with agentic coding practices, prompt engineering, and LLM concepts.