Kafka Data Engineer
About the role
The opportunity involves organizing big data from various sources to yield insights. You will be responsible for designing, developing, and deploying Kafka clusters in a cloud environment, managing Kafka Schema Registry and Kafka Security Manager, guiding and mentoring team members, and overseeing scalable platform development.
Responsibilities
- Design, develop, and deploy Kafka clusters in Kubernetes in AWS
- Utilize Kafka Schema Registry and Kafka Security Manager for schema evolution and security
- Guide and mentor data engineers, developers, and data consumers
- Assess, design, build, and maintain scalable platforms for clients
Requirements
- Experience with Kafka
- Experience with data partitioning strategies and topic monitoring
- Experience deploying and upgrading Kafka clusters in high availability containerized environments
- Experience with observability platforms like Elastic or Datadog for monitoring data pipelines
- Knowledge of stream processing pipelines and analytics
- Secret clearance
Qualifications
- High school diploma or GED
- Experience with Apache NiFi
- Experience with multi-cluster or containerized environments
- Experience with scripting in Bash or Python
- Experience deploying and maintaining applications, appliances, or machines aligned to DoD STIG and SRG
- Experience with automation tools like Terraform, Ansible, or Puppet for IaC and CaC
- Knowledge of cybersecurity concepts
Skills
- Knowledge of cybersecurity concepts
- Experience with encryption, threat detection, and supply chain risk management
Benefits
Full-time and part-time employees are eligible for a variety of benefits including health, life, disability, financial, and retirement benefits, as well as paid leave, professional development, tuition assistance, work-life programs, and dependent care. The company also offers recognition awards and a competitive salary range of $77,600 to $176,000 annually.
Pay
The estimated annual salary range for this position is $77,600 to $176,000.
Schedule
Work model varies depending on the position type (remote, hybrid, or onsite).