Kafka Engineer

Americana Restaurants; Mohali; Sur place; INR 2 000 000 - 4 000 000; Plein temps

Résumé du poste

Americana Restaurants in Mohali, India is seeking an experienced Kafka platform engineer to design, deploy, and manage highly available Kafka and Confluent environments. You will work on production clusters, develop data pipelines, and implement security and governance practices.

The role requires 4+ years of hands-on Kafka experience, plus skills in CI/CD, IaC, Python, Docker, Kubernetes, and cloud platforms.

Qualifications

• 4+ years of hands-on experience managing Kafka-based streaming platforms.
• Expertise in Kafka Connect and Kafka Streams; cluster administration and performance tuning.
• Production support and troubleshooting; security, governance, and access controls.
• Experience with CI/CD pipelines and Infrastructure as Code.
• Proficiency in Python, shell scripting, or other automation tools.
• Experience with cloud platforms such as AWS, Azure, or GCP.
• Docker and Kubernetes.
• Bachelor's degree in Computer Science, Engineering, or a related field.
• Confluent Certified Administrator or Developer certification.
• Experience with large-scale event-driven architectures and microservices.
• Proven track record of improving platform reliability, reducing incidents, and optimizing operational costs.

Responsabilités

• Design, build, and manage highly available Kafka and Confluent Platform environments.
• Configure, deploy, and support Kafka clusters in production environments.
• Develop and maintain Kafka Connect, Kafka Streams, and event-driven data pipelines.
• Automate Kafka infrastructure using Terraform, CI/CD pipelines, and Infrastructure as Code practices.
• Enhance platform reliability through HA/DR strategies, capacity planning, monitoring, and proactive performance tuning.
• Implement Kafka security best practices, including RBAC, ACLs, and service account management.
• Drive cost optimization initiatives through cluster right-sizing, retention tuning, and resource efficiency improvements.
• Troubleshoot complex streaming platform issues and ensure SLA/SLO adherence.
• Collaborate with engineering teams to support microservices and event-driven architectures.

Connaissances

Kafka

Kafka Connect

Kafka Streams

Cluster administration

Troubleshooting

Security & governance

CI/CD pipelines

Infrastructure as Code

Python

Shell scripting

Cloud platforms

Docker

Kubernetes

Communication skills

Analytical thinking

Formation

Bachelor's degree in CS/Engineering

Confluent Certification

Outils

Terraform

Description du poste

4+ years of hands-on experience managing Kafka-based streaming platforms

Strong expertise in:

• Kafka Connect & Kafka Streams
• Kafka cluster administration and performance tuning
• Production support and troubleshooting
• Security, governance, and access controls

Experience with:

• CI/CD pipelines and Infrastructure as Code
• Python, Shell Scripting, or other automation tools
• Cloud platforms such as AWS, Azure, or GCP
• Docker and Kubernetes

Strong analytical, problem-solving, and communication skill

Preferred Qualifications

• Bachelor's degree in Computer Science, Engineering, or a related field.
• Confluent Certified Administrator or Developer certification.
• Experience with large-scale event-driven architectures and microservices.
• Proven track record of improving platform reliability, reducing incidents, and optimizing operational costs.

What You'll Do

• Design, build, and manage highly available Kafka and Confluent Platform environments.
• Configure, deploy, and support Kafka clusters in production environments.
• Develop and maintain Kafka Connect, Kafka Streams, and event-driven data pipelines.
• Automate Kafka infrastructure using Terraform, CI/CD pipelines, and Infrastructure as Code practices.
• Enhance platform reliability through HA/DR strategies, capacity planning, monitoring, and proactive performance tuning.
• Implement Kafka security best practices, including RBAC, ACLs, and service account management.
• Drive cost optimization initiatives through cluster right-sizing, retention tuning, and resource efficiency improvements.
• Troubleshoot complex streaming platform issues and ensure SLA/SLO adherence.
• Collaborate with engineering teams to support microservices and event-driven architectures.