Développeuse/Développeur DevOps

As a Développeuse/Développeur DevOps at Coactive, you will be responsible for designing and maintaining scalable infrastructure essential for supporting microservices and data pipelines. You'll focus on developing CI/CD pipelines, managing real-time data workflows, and ensuring that our cloud environments are secure and reliable.

Candidates for the Développeuse/Développeur DevOps role should ideally have over five years of experience in cloud infrastructure, particularly with AWS, GCP, and Azure. A strong background in Kubernetes, CI/CD practices, monitoring tools, and programming in Python are also essential for the role.

At Coactive, Développeuses/Développeurs DevOps engage with a variety of technologies, including AWS, GCP, Azure, Kubernetes, Terraform, Kafka, Spark, and Datadog. You'll be deeply involved in automating infrastructure and enhancing data management workflows using these dynamic tools.

Coactive fosters a supportive and innovative work environment where creativity thrives. This is a hybrid position based in Montreal, ensuring flexibility and promoting a healthy work-life balance, with a focus on collaboration and personal development in the tech space.

Coactive is dedicated to employee growth and offers numerous opportunities for career advancement. As part of our team, you'll gain exposure to cutting-edge technologies and industry best practices, collaborate with talented experts, and continuously enhance your skills in the evolving field of AI and DevOps.

In your response, highlight specific instances where you deployed, scaled, or managed applications using Kubernetes. Mention any related tools such as Envoy or Keda, and discuss the impact of your work on project efficiency and scalability.

Explain your methodology for assessing needs and designing the architecture, including considerations for cost, reliability, and scalability in AWS, GCP, or Azure because these platforms are crucial for the role at Coactive.

Discuss your processes for enhancing CI/CD, such as incorporating automated tests or reducing build times. Illustrate how these practices improve deployment frequency and reduce lead time on new features.

Talk about your experience in implementing best practices for cloud security, including user authentication, network security measures, and regular audits to ensure compliance and data integrity.

Detail a project where you worked with technologies like Kafka or Spark to handle streaming data. Discuss any challenges you faced and how you overcame them, focusing on efficiency and system reliability.

Explain how you utilize Python for automation, such as scripting and managing infrastructure, and mention specific tools or libraries you use to streamline processes within your DevOps practices.

Provide examples of how you have used Datadog or similar tools to implement monitoring solutions, including key metrics tracked and how you used the insights to enhance system performance and reliability.

Discuss your commitment to continuous learning through resources such as online courses, webinars, networking events, attending conferences, and following key industry blogs or thought leaders.

Share a specific incident where troubleshooting was required, detailing the steps you took to diagnose the problem, the tools you used, and how you communicated with your team throughout the process.

Elaborate on the importance of clear communication, shared goals, and an understanding of workflow requirements between DevOps and ML teams. Highlight your strategies for fostering teamwork and ensuring smooth project execution.