Experience: 10+ Years
Visa: EAD, L2, E2, TN, (No H1B & GC)
Job Description
Version Control Systems: Atlassian Bitbucket, GitHub, GitLab.
* Containerization and Orchestration: Docker, Kubernetes, Red Hat OpenShift.
* Streaming Platforms: Confluent Platform (Kafka), Apache Kafka, Schema Registry, Kafka Connect, Control Center, ksqlDB.
* Configuration Management and Infrastructure as Code (IaC): Ansible, Terraform, Chef.
* Cloud Computing Platforms: Amazon Web Services (AWS), Google Cloud Platform (Google Cloud Platform), Microsoft Azure.
* Build and Automation Tools: Jenkins, Maven, Gradle, GitLab CI/CD.
* Continuous Integration and Continuous Deployment (CI/CD): Jenkins, Ansible, GitLab CI/CD.
* Operating Systems and Scripting: Red Hat Enterprise Linux, Bash Shell Scripting, Python, JavaScript.
* Experience with Kafka cluster deployment, upgrades, migrations, and multi-region implementations.
* Linux/Unix administration and performance tuning.
* Enterprise security, SSL/TLS, mTLS, RBAC, ACLs, and certificate lifecycle management.
* Monitoring and Observability: Dynatrace, Splunk, Prometheus, Grafana, Confluent Control Center.
* Disaster Recovery, Cluster Linking, Replication, and High Availability architectures.
* AI-assisted development tools such as Microsoft Copilot, Amazon Kiro and AI-powered DevOps automation platforms.
* Confluent for Kubernetes (CFK) deployment, administration, and lifecycle management.
* Experience deploying and managing Kafka Connect clusters using CFK on OpenShift and Kubernetes.
* Expertise in Kubernetes Operators, Custom Resource Definitions (CRDs), StatefulSets, and containerized Kafka workloads.
• Experience with GitOps and CI/CD-driven Kafka Connect deployments using CFK, Ansible, Jenkins, bitbucket.
• Knowledge of Kafka Connect plugin management, connector scaling, fault tolerance, and high availability.
* Experience leveraging AI tools to automate deployments, troubleshooting, documentation, code generation, operational workflows, and platform support activities.
* Coordination with Network, Storage, Security, Infrastructure, Cloud, and Application teams.
Support the Kafka Engineering Team in onboarding applications, connectors, producers, consumers, and streaming workloads through automated CI/CD pipelines.
Design, deploy, administer, and maintain Confluent Platform components including Kafka Brokers, KRaft Controllers, Schema Registry, Kafka Connect, Control Center
Develop and automate Kafka infrastructure deployments using Ansible, Terraform, Jenkins, Git repositories, and Infrastructure-as-Code frameworks.
Implement and support Kafka services on OpenShift, Kubernetes, cloud, and hybrid environments.
Assist application teams in troubleshooting Kafka connectivity, performance, messaging, schema, and integration issues.
Configure and support Kafka Connect source and sink connectors, data pipelines, and platform integrations.
Implement and maintain RBAC, ACLs, SSL/TLS, mTLS, encryption, certificate management, and security controls.
Perform lifecycle management of SSL/TLS certificates including provisioning, rotation, renewal, auditing, and revocation.
Design and validate Disaster Recovery (DR), Cluster Linking, replication, failover, and resilience solutions.
Monitor Kafka platform health, capacity, availability, consumer lag, throughput, latency, and operational metrics.
Apply platform upgrades, patches, security remediations, and software lifecycle management activities.
Leverage AI-powered tools such as GitHub Copilot, Microsoft Copilot, and Amazon Kiro to improve engineering productivity, automate repetitive operational tasks, accelerate troubleshooting, and generate technical documentation.
Develop AI-enabled automation solutions for Kafka onboarding, connector deployment, configuration validation, operational runbooks, incident response, and platform governance.
Partner with Infrastructure, Security, Network, Cloud, and Application teams to deliver secure, scalable, and resilient streaming platforms.
Create and maintain operational runbooks, platform standards, architecture documentation, and disaster recovery procedures.
Drive continuous improvement initiatives through automation, AI-assisted engineering practices, self-service capabilities, and platform modernization.
