Negotiable
Outside
Remote
USA
Summary: The role of DevOps Lead Engineer with expertise in Confluent Kafka involves leading the design, deployment, and optimization of large-scale event-streaming environments across on-premise and cloud infrastructures. The position requires extensive experience in DevOps practices, particularly with Confluent Kafka and AWS, to automate and streamline engineering workflows. The ideal candidate will also provide architectural leadership for event-driven solutions and manage high-severity production incidents. This is a contract-to-hire position with a remote working arrangement.
Key Responsibilities:
- Design, deploy, and configure Confluent Kafka clusters, topics, partitions, replication strategies, and security configurations across on-prem and cloud environments (including Confluent Cloud).
- Automate provisioning, deployment, scaling, and maintenance using tools such as Terraform, Chef, Ansible, Jenkins, and other CI/CD technologies.
- Build automated, self-service capabilities for topic creation, schema governance, ACLs, and resource provisioning to streamline engineering workflows.
- Build and maintain CI/CD pipelines integrating Kafka components and infrastructure changes using Jenkins, Git, and other DevOps toolchains.
- Perform root-cause analysis, optimize throughput, tune brokers/producers/consumers, and manage high-severity production incidents.
- Provide architectural leadership for event-driven solutions, real-time data processing, and streaming ecosystems across cloud and hybrid environments.
Key Skills:
- 10+ years of experience in DevOps, Cloud Engineering, or Platform Engineering roles.
- Hands-on expertise with Confluent Kafka (Cloud and On-Prem).
- Advanced knowledge of AWS (VPC, IAM, Networking, Security, EKS nice to have).
- Strong proficiency in Terraform.
- Strong CI/CD experience with Jenkins, Git, and automated deployment pipelines.
- Experience managing and monitoring large-scale distributed systems.
- Strong understanding of event-driven architecture, data streaming patterns, and real-time integration.
- Excellent communication and leadership skills with the ability to collaborate across teams.
Salary (Rate): undetermined
City: undetermined
Country: USA
Working Arrangements: remote
IR35 Status: outside IR35
Seniority Level: undetermined
Industry: IT
Role: Devops Lead Engineer with Confluent Kafka
Location-Remote
Mode Of hire- Contract to hire
We are seeking a highly skilled DevOps Lead Engineer with expertise in Confluent Kafka, AWS, and modern automation frameworks. The ideal candidate will lead the design, deployment, and optimization of large-scale, distributed event-streaming environments across on-premise and cloud infrastructures.
Key Responsibilities
- Design, deploy, and configure Confluent Kafka clusters, topics, partitions, replication strategies, and security configurations across on-prem and cloud environments (including Confluent Cloud).
- Automate provisioning, deployment, scaling, and maintenance using tools such as Terraform, Chef, Ansible, Jenkins, and other CI/CD technologies.
- Build automated, self-service capabilities for topic creation, schema governance, ACLs, and resource provisioning to streamline engineering workflows.
- Build and maintain CI/CD pipelines integrating Kafka components and infrastructure changes using Jenkins, Git, and other DevOps toolchains.
- Perform root-cause analysis, optimize throughput, tune brokers/producers/consumers, and manage high-severity production incidents.
- Provide architectural leadership for event-driven solutions, real-time data processing, and streaming ecosystems across cloud and hybrid environments.
Skill set requirement:
- 10+ years of experience in DevOps, Cloud Engineering, or Platform Engineering roles.
- Hands-on expertise with Confluent Kafka (Cloud and On-Prem).
- Advanced knowledge of AWS (VPC, IAM, Networking, Security, EKS nice to have).
- Strong proficiency in Terraform.
- Strong CI/CD experience with Jenkins, Git, and automated deployment pipelines.
- Experience managing and monitoring large-scale distributed systems.
- Strong understanding of event-driven architecture, data streaming patterns, and real-time integration.
- Excellent communication and leadership skills with the ability to collaborate across teams.