Cloud Infrastructure : Architect, manage, and scale all aspects of cloud infrastructure primarily in AWS, leveraging Terraform for automation and efficiency.
CI/CD & DevOps Practices: Design and implement CI/CD pipelines to streamline deployment and improve efficiency.
Monitoring & Observability: Establish robust monitoring, logging, and auditing measures to ensure best practices for system observability, easy debugging and reliability.
Containers & Kubernetes: Deploy and manage containerized applications using ArgoCD, Kubernetes, Docker, and Helm.
Collaboration & Leadership: Work cross-functionally to optimize workflows, drive automation, and improve infrastructure scalability.
Automation - Automate deployment processes to enhance efficiency and minimize downtime.
Databases: Manage databases for high availability and performance.
Requirements
5+ years of experience in a DevOps role, with a focus on AWS cloud infrastructure.
Strong expertise in Terraform for Infrastructure as Code (IaC).
Proven experience designing, implementing, and optimizing CI/CD pipelines.
Strong experience with managing GCP environments.
Proven experience with creating new architectures for cloud infrastructure.
Experience with supporting Analytics services such as Redshift, Snowflake, etc.
Strong knowledge of Kubernetes, Helm, and container orchestration.
Proficiency in automation and scripting with Python, Bash, or Go.
Strong understanding of cloud security best practices and compliance frameworks.
Excellent problem-solving skills and the ability to troubleshoot complex issues in a fast-paced environment.
Strong communication skills and ability to collaborate with cross-functional teams.
Advantages
Deep understanding of monitoring and observability tools such as Kibana, Prometheus, Grafana, and Datadog.
Familiarity with event-driven architectures and message queues (Kinesis, SQS, RabbitMQ).
Hands-on experience managing cloud databases and optimizing performance.
Experience with HashiCorp tools such as Consul and Vault.
Experience in machine learning infrastructure and data engineering workflows.