Job Description: Senior DevOps Engineer Kubernetes, Kafka & Python Automation

Location: Massachusetts- Onsite
Experience: 7+ years

Job Summary

We are seeking an experienced Senior DevOps Engineer with strong expertise in Kubernetes, Apache Kafka, Python automation, and CI/CD. The ideal candidate will be responsible for designing, implementing, automating, and supporting highly available cloud-native infrastructure and event-driven platforms.

The candidate must have strong hands-on experience with Kubernetes administration and troubleshooting, Kafka platform operations, and Python-based automation. This role requires close collaboration with development, infrastructure, and application teams to improve deployment velocity, platform reliability, scalability, and operational efficiency.

Work from the office is mandatory 4 days per week. Candidates local to Massachusetts are strongly preferred.

Key Responsibilities

  • Design, deploy, configure, and manage Kubernetes clusters in production environments.
  • Perform Kubernetes administration, including deployments, services, ingress, namespaces, RBAC, ConfigMaps, Secrets, StatefulSets, persistent volumes, and autoscaling.
  • Troubleshoot complex Kubernetes issues involving pods, nodes, networking, resource utilization, deployments, and application failures.
  • Manage and support Apache Kafka infrastructure, including brokers, topics, partitions, replication, consumer groups, and Kafka Connect.
  • Monitor and troubleshoot Kafka consumer lag, broker failures, under-replicated partitions, throughput, connectivity, and performance issues.
  • Develop Python automation scripts to automate infrastructure provisioning, application deployment, monitoring, health checks, operational tasks, and remediation.
  • Build and maintain robust CI/CD pipelines using Jenkins, GitLab CI/CD, GitHub Actions, or similar tools.
  • Automate infrastructure provisioning and configuration using Terraform and Ansible.
  • Containerize applications using Docker and deploy workloads using Kubernetes and Helm.
  • Implement monitoring, alerting, and observability using tools such as Prometheus, Grafana, Datadog, Splunk, or ELK.
  • Develop dashboards and alerts for Kubernetes cluster health, Kafka performance, application availability, and infrastructure metrics.
  • Implement secure Kafka environments using SSL/TLS, SASL, ACLs, authentication, and authorization.
  • Participate in production incident management, troubleshooting, root-cause analysis, and preventive remediation.
  • Support Kubernetes upgrades, application releases, rollback procedures, disaster recovery, and capacity planning.
  • Work closely with software engineers to optimize applications for cloud-native and event-driven architectures.
  • Establish DevOps best practices around automation, infrastructure-as-code, release management, monitoring, and operational reliability.
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