Site Reliability Engineer

The Modern Data Company is redefining data management for the AI era, transforming data from a technical challenge into a company’s most powerful business asset. Modern's DataOS platform is the world's first operating system for data, providing a breakthrough layer that integrates with any data stack, no rip and replace.

Fortune 1000+ enterprises use DataOS to scale AI and solve mission-critical data challenges. With DataOS, enterprises are accelerating AI adoption by up to 90% while reducing data consumption and platform costs by 50%. Modern’s rapidly expanding customer base includes global category leaders across a wide range of global industries. They trust DataOS to power their AI and business transformation.

About the Role

We’re looking for a SRE to join our team and help drive the reliability, scalability, and efficiency of our platforms across multi-cloud environments. You’ll be instrumental in shaping observability, automation, and operational excellence while partnering closely with platform engineering and product teams to build robust monitoring systems.

Key Responsibilities

• Design and maintain observability stacks (Prometheus, Thanos, Grafana) for real-time system health and alerting.
  
• Lead APM and log analytics implementation to reduce MTTR and proactively manage system performance.
  
• Collaborate with product and platform teams to ensure high availability and scalability across cloud regions.
  
• Automate operational processes (incident response, infra provisioning, deploys) using scripting and Infrastructure-as-Code.
  
• Build resilient CI/CD pipelines to support rapid and safe deployments.
  
• Optimize infrastructure usage and cost across AWS, Azure, and GCP.
  
• Lead incident response, conduct RCA, and drive systemic fixes across teams.
  
• Define and document playbooks, reliability standards, and best practices.

Requirements

• 5+ years of experience in SRE or DevOps roles with production ownership.
  
• Deep knowledge of observability tools (Prometheus, Thanos, Grafana) and logging frameworks.
  
• Strong expertise with Kubernetes, Docker, Terraform, and cloud-native architectures.
  
• Proven experience in automating workflows using Python, Bash, or similar scripting languages.
  
• Hands-on experience with AWS, Azure, and/or GCP.
  
• Strong problem-solving mindset, with a bias for automation and scalability.
  
• Clear communication, and a drive for continuous learning and collaboration.

Benefits