Staff DevOps Engineer

As a Staff DevOps Engineer at SamCart, you will design and operate cloud-based infrastructure on AWS, focusing on Docker and Kubernetes. Your responsibilities will include supporting the development of a multi-tenant application, performing DevOps functions like system administration and configuration management, ensuring efficient deployments, and leading migrations from GCP to AWS.

To thrive as a Staff DevOps Engineer at SamCart, candidates should possess expert knowledge of Amazon Web Services and advanced tooling like Docker, Kubernetes, and Terraform. You should have at least 5 years of experience in cloud infrastructure, proficiency in Python and modern scripting languages, and familiarity with GCP for seamless migration support.

At SamCart, our culture embraces transparency, creativity, and compassion. As a Staff DevOps Engineer, you'll be part of a diverse team that values open communication, unique perspectives, and continuous growth. We believe in balancing professional success with personal well-being, making sure our team loves their job at least 80% of the time.

SamCart supports work-life balance for our Staff DevOps Engineers with unlimited PTO and an encouraged 14-day minimum. We understand the importance of personal time and strive to create a healthy environment where our team members can recharge and thrive.

Career growth is essential at SamCart, especially for our Staff DevOps Engineers. We provide avenues for professional development and continuous learning to help you build a sustainable, adaptable career. You'll have the opportunity to work on challenging projects and collaborate with industry experts.

In my previous roles, I have extensively worked with AWS services including EC2, S3, and Lambda. I demonstrate a strong understanding of how to design scalable and highly available applications, ensuring optimal performance while adhering to best practices.

I prioritize using tools like GitHub Actions and Jenkins to automate my CI/CD processes. My approach focuses on creating a reliable pipeline that allows for fast and efficient code integration, testing, and deployment while maintaining quality through rigorous monitoring.

Ensuring security in the cloud involves using tools like SOPS for secret management and adhering to the principle of least privilege for access controls. I regularly conduct audits and assessments to identify vulnerabilities and work proactively to address them.

I have hands-on experience deploying applications in Kubernetes, managing services, and orchestrating scaling events. My approach includes writing Helm charts for reproducibility and ensuring proper monitoring and logging to maintain performance.

I implement multi-region backups and have a tested disaster recovery plan in place. Regularly testing recovery strategies ensures that data integrity is maintained, and I leverage automated backups through cloud services to minimize downtime.

In a previous role, migrating services between platforms posed significant risks. I mitigated this by developing a detailed migration plan, conducting thorough testing after each stage, and involving stakeholders to ensure all needs were met, which ultimately ensured a smooth transition.

I have experience using Terraform for infrastructure as code, enabling me to manage infrastructure through code rather than manual processes. This has resulted in repeatable deployments and a more agile development workflow.

I continually engage with the community through forums, online courses, and webinars. Additionally, I participate in local meetups and follow industry leaders to stay updated on new technologies and best practices, ensuring that my skills remain relevant.

I prioritize open communication and believe in establishing strong relationships with engineering teams. Regular check-ins, feedback sessions, and joint problem-solving allow us to align our objectives and work more effectively together.

To optimize performance, I regularly monitor application metrics and logs. I also use autoscaling features in AWS and adjust resource allocation based on load tests to ensure applications can handle traffic efficiently while minimizing costs.