Site Reliability Engineer

Cisco is hiring a Site Reliability Engineer in Bangalore.

Site Reliability Engineer — NADP Platform Location Bangalore, India — Hybrid Team

Responsibilities

• Own and operate scalable, reliable, and cost-efficient infrastructure for the ThousandEyes Network Assurance Data Platform.

• Manage, optimize, and improve large-scale data workflows using Apache Airflow, AWS EMR, Spark, and Hadoop-based processing platforms.

• Operate and improve Amazon EKS environments supporting containerized services, ML workloads, and production-grade platform components.

• Build and maintain infrastructure automation using Terraform and other infrastructure-as-code practices.

• Develop Python-based automation, integrations, operational tooling, reporting, and reliability improvements.

• Drive FinOps practices across NADP infrastructure, including cost visibility, cost allocation, forecasting, anomaly detection, optimization, and governance.

• Partner with data engineering, ML, platform, finance, and product teams to improve reliability, performance, scalability, and cost efficiency.

• Identify infrastructure bottlenecks, performance issues, inefficient workloads, and cost optimization opportunities.

• Improve observability, alerting, incident response, and operational readiness across data and ML platforms.

• Support capacity planning, right-sizing, autoscaling, storage optimization, and workload efficiency across AWS services.

• Lead technical discussions, influence design decisions, and guide teams toward reliable and cost-conscious architecture.

• Provide senior-level technical leadership, mentorship, and operational guidance to engineers across the team.

• Drive continuous improvement in platform reliability, automation, deployment practices, and operational excellence.

Requirements

• Bachelor’s degree or higher in Engineering, Computer Science, or equivalent practical experience.

• 8–10 years of relevant experience in Site Reliability Engineering, DevOps, Cloud Infrastructure, Platform Engineering, Data Infrastructure, or Production Engineering.

• Strong hands-on experience operating production infrastructure on AWS.

• Strong experience with Apache Airflow for workflow orchestration, pipeline operations, scheduling, monitoring, and troubleshooting.

• Hands-on experience with AWS EMR, Spark, Hadoop, or similar large-scale data processing platforms.

• Strong experience operating Amazon EKS or Kubernetes-based environments in production.

• Experience supporting containerized workloads, preferably including ML workloads or data platform services.

• Strong hands-on experience with Terraform and infrastructure-as-code practices.

• Strong Python programming or scripting experience for automation, integrations, operational tooling, and infrastructure workflows.

• Practical experience with cloud cost optimization, FinOps, AWS cost analysis, tagging, budgeting, forecasting, and cost governance.

• Strong understanding of Linux systems, networking, distributed systems, and production troubleshooting.

• Experience with observability tools such as CloudWatch, Prometheus, Grafana, Splunk, OpenSearch, Datadog, or similar platforms.

• Experience with incident management, production support, root cause analysis, reliability improvements, and operational excellence.

• Ability to analyze infrastructure, performance, and cost data and convert findings into clear technical recommendations.

• Strong communication skills with the ability to collaborate across data, ML, platform, finance, and engineering teams.

• Ability to operate independently, drive initiatives end to end, and provide technical leadership in a fast-paced environment.

Preferred qualifications

• Experience working with large-scale SaaS platforms or high-volume data infrastructure.

• Experience with ML infrastructure, model execution platforms, batch processing, or data pipeline reliability.

• Experience optimizing EMR, Spark, Airflow, EKS, storage, and compute workloads for performance and cost.

• Experience with AWS services such as EC2, S3, RDS, IAM, VPC, CloudWatch, OpenSearch, Lambda, ElastiCache, and related cloud-native services.

• Experience with AWS Savings Plans, Reserved Instances, Spot adoption, Graviton migration, storage lifecycle management, and workload right-sizing.

• Experience with cloud cost management tools such as AWS Cost Explorer, AWS CUR, Cloudability, CloudHealth, Kubecost, or similar platforms.

• Experience driving FinOps programs, cost reviews, stakeholder reporting, OKR tracking, and executive-level updates.

• Experience with CI/CD systems, GitHub workflows, Atlantis, or similar deployment automation platforms.

• Experience with Puppet, Ansible, Helm, Argo CD, or other configuration and deployment management tools.

• FinOps certification or equivalent hands-on cloud financial management experience is a plus.

• Ability to influence engineering teams toward cost-aware, scalable, and reliable design patterns.

What Success Looks Like

• NADP data and ML infrastructure is reliable, scalable, performant, and cost-efficient.

• Airflow, EMR, Spark, and EKS workloads are operated with strong observability, automation, and production maturity.

• AWS cost visibility, forecasting, and governance are improved across NADP-owned infrastructure.

• Cloud wastage is reduced through right-sizing, automation, storage optimization, and workload efficiency improvements.

About Cisco

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