Staff Engineer DevOps, Data Security (DLP)

**About the Role** *Please note, this team is hiring across multiple levels. Candidates will be individually assessed and appropriately leveled based on their skills and experience.* The Netskope Data Security team is focused on providing unrivaled visibility and real-time data protection. Our products help ensure that customers' data is protected wherever it lives. Our engineers architect, build, test, deploy, and operate highly scalable, high-performance data protection services across public cloud, private cloud, and on-premises environments. In this role, you will help build and operate the infrastructure, automation, and engineering platforms that enable our Data Security services to be deployed and operated reliably at global scale. You will work closely with development, SRE, Platform Engineering, Operations, QA, and cloud infrastructure teams. You can read more about our best-in-class Data Security solutions at [Netskope One Data Security](https://www.netskope.com/solutions/data-protection). **What's in It for You?** We are looking for DevOps engineers who enjoy solving complex infrastructure and production engineering problems through a combination of software development, automation, and strong systems knowledge. You will have the opportunity to work across Kubernetes, cloud infrastructure, CI/CD, observability, networking, and distributed systems while developing tools and automation that improve how our engineering teams build, deploy, and operate services. You will also have opportunities to use modern AI-assisted development tools to accelerate automation, software development, troubleshooting, and engineering productivity. **What You Will Be Doing** - Deploy, operate, and troubleshoot Kubernetes-based services across public cloud, private cloud, and on-premises environments. - Build and maintain automation for deployments, releases, configuration management, infrastructure, and operational workflows. - Develop tools and software that improve the reliability, scalability, and efficiency of our services and engineering processes. - Work with development, SRE, Platform Engineering, Operations, QA, cloud providers, and other teams to resolve complex production and deployment issues. - Improve monitoring, metrics, logging, dashboards, and alerting to provide strong visibility into application and infrastructure health. - Investigate complex issues spanning applications, Kubernetes, networking, infrastructure, and cloud platforms, and drive them through root cause and resolution. - Identify repetitive or operationally expensive processes and replace them with reliable automation and tooling. - Help improve service scalability, performance, capacity management, and operational readiness. - Contribute to runbooks, operational procedures, and engineering best practices. - Participate in the team's production support and on-call rotation. - Use AI-assisted development tools and coding agents as part of day-to-day engineering to accelerate development of automation, tooling, testing, troubleshooting, and operational solutions. **Required Skills and Experience** - 5+ years of experience in DevOps, Site Reliability Engineering, Platform Engineering, infrastructure engineering, or a related role. Staff-level candidates will typically have **8+ years of relevant experience**. - Strong hands-on experience with Linux and troubleshooting production systems. - Experience deploying and operating Kubernetes-based services in production. - Experience with at least one major public or private cloud platform such as AWS, GCP, Azure, or OpenStack. - Solid understanding of networking fundamentals including TCP/IP, DNS, load balancing, SSL/TLS, and cloud or Kubernetes networking. - Programming and automation experience using Python, Go, or a similar language. - Experience with CI/CD, infrastructure automation, or configuration management using tools such as Jenkins, Ansible, Terraform, or equivalent technologies. - Experience with production monitoring and observability using technologies such as Prometheus, Grafana, Sumo Logic, Elastic Stack, or equivalent platforms. - Strong troubleshooting and problem-solving skills across applications and infrastructure. - Ability to independently own and deliver technical projects. - Strong written and verbal communication skills and the ability to collaborate effectively with geographically distributed teams. - Hands-on experience using AI-assisted development tools and coding agents to accelerate software development, automation, testing, debugging, and problem solving, with the ability to review, validate, and take ownership of AI-generated code. **Preferred Qualifications** - Experience building internal platforms, developer tooling, release automation, or other systems that improve engineering productivity. - Experience troubleshooting distributed systems and large-scale cloud services. - Strong software engineering practices, including code review, testing, debugging, and maintainability. - Experience working across multiple cloud or hybrid-cloud environments. **Education** BS in Computer Science, Engineering, or equivalent practical experience required. An advanced degree is strongly preferred. #LI-AB1