Strategy to Hire a Skilled DevOps Engineer

Your ultimate checklist for how to hire a DevOps Engineer. Includes what to look for while hiring DevOps Engineer, skills to test, capabilities based on experience level, sample questions and a ready-to-use DevOps Engineer assessment.

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How to hire a DevOps Engineer

Specifications for a DevOps Engineer

Deciding on a Tech Stack for a DevOps Engineer

Hiring a DevOps Engineer requires a focus on technical skills essential for bridging the gap between software development and operations. Key skills include:

  • Continuous Integration/Continuous Deployment (CI/CD): Understanding of automation tools and pipelines for efficient code deployment.
  • Cloud Services (AWS, Azure, GCP): Proficiency in cloud platforms for scalable infrastructure management.
  • Containerization (Docker, Kubernetes): Knowledge of container orchestration to ensure consistent environments across development, testing, and production.
  • Scripting and Automation (Python, Bash): Ability to automate repetitive tasks and configure systems using scripting languages.
  • Infrastructure as Code (IaC): Experience with tools like Terraform and Ansible for managing infrastructure through code.

Assessing skills of a DevOps Engineer

Assessing a candidate's DevOps skills involves reviewing their experience with CI/CD pipelines, cloud services, containerization, scripting, and IaC. Practical tests or projects that simulate real-world scenarios can help evaluate their proficiency in automating and optimizing development and deployment processes.

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Concepts your DevOps Engineer should know based on experience

DevOps Engineers assessed using Equip’s assessments

Entry-level DevOps Engineer

396

Mid-senior DevOps Engineer

137

Senior DevOps Engineer

73

  • Version Control Systems (e.g., Git): Understanding the importance of source code management.
  • Basic Cloud Services: Familiarity with cloud computing basics, especially in AWS or Azure.
  • Simple Automation Scripts: Ability to write basic scripts for task automation.

  • CI/CD Tools (Jenkins, GitLab CI): Knowledge of setting up and managing pipelines.
  • Infrastructure Monitoring: Understanding of monitoring tools and practices for system health.
  • Security Best Practices: Awareness of security principles in the DevOps process.

  • Complex Cloud Architectures: Designing and managing scalable and resilient cloud infrastructure.
  • Microservices and Container Orchestration: Deep understanding of deploying and managing containerized applications.
  • Advanced IaC Strategies: Proficiency in using IaC for complex infrastructure management.

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About DevOps Engineer

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Ezra V

Recruiter
HR Recruiter
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Really helpful to screen candidates!
The auto-generated tests and marking scheme are the best features. I have been able to hire around 12 candidates using Equip, eliminating the need for manual screening.

DevOps Engineers play a pivotal role in bridging the gap between software development and IT operations, ensuring seamless integration and continuous delivery (CI/CD) of software. They automate and streamline processes, manage cloud infrastructure, and deploy containerized applications, enabling faster and more efficient production cycles. With skills in scripting, cloud services, and system monitoring, DevOps Engineers contribute significantly to the agility and performance of technology teams.

1. Importance of DevOps Engineer

  • Enhanced Collaboration: They foster a culture of collaboration between developers and operations teams.
  • Increased Efficiency: Automation of deployment and monitoring processes speeds up development cycles.
  • Improved Reliability: Continuous integration and delivery ensure software quality and stability.
  • Scalability: Expertise in cloud services enables scalable infrastructure management.
  • Security: Incorporating security practices into the development process to safeguard against vulnerabilities.

2. Recent Industry Trends for DevOps Engineers

  • Shift towards Cloud-Native Technologies: Increased adoption of cloud services and containerization.
  • Infrastructure as Code (IaC): Growing reliance on IaC for efficient infrastructure management.
  • Microservices Architecture: Preference for microservices over monolithic designs for enhanced scalability.
  • Emphasis on Security (DevSecOps): Integrating security early in the development process.
  • AI and Machine Learning in DevOps: Leveraging AI to optimize operations and automate decision-making.

3. Popular Frameworks for DevOps Engineers

  • Jenkins: For automating CI/CD pipelines.
  • Docker: Containerization platform to package and deploy applications.
  • Kubernetes: Orchestration tool for managing containerized applications.
  • Terraform: IaC tool for provisioning and managing cloud resources.
  • Ansible: Automation tool for configuration management and application deployment.

How Equip helps you hire a DevOps Engineer

Seamless hiring made easy in 3 simple steps
1
Create & Share assessment
Using Equip's Question Banks, or add your own questions
2
Candidates finish assessment remotely
Typically, 30 mins to 1 hour. With anti-cheating measures
3
Shortlist only the best performing candidates
Equip automatically evaluates candidates' responses

Frequently Asked Questions

While both aim to improve software delivery and reliability, DevOps focuses on the collaboration and automation between development and operations, whereas Site Reliability Engineering (SRE) applies a software engineering approach to solve operational problems and ensure scalable and reliable systems.

Cloud computing provides scalable and flexible resources that DevOps teams can manage and automate through cloud services, enhancing the deployment, scaling, and management of applications.

Yes, a proficient DevOps Engineer often works across multiple cloud platforms (e.g., AWS, Azure, GCP) to leverage the unique benefits of each for optimized infrastructure solutions.

Python is favored for its simplicity and versatility, making it ideal for scripting automation tasks, infrastructure management, and data analysis within DevOps practices.

In machine learning projects, DevOps Engineers facilitate continuous integration and delivery of ML models, manage scalable cloud infrastructure, and ensure efficient deployment and monitoring of ML applications.

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Last updated: November 04, 2025