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Senior Big Data DevOps Engineer (Kafka/AWS)

NEXIFY INFOSYSTEMS LLCSt. Louis, MO🇺🇸United StatesPosted 20 Jul 2026

Why This Role Stands Out

Advance your career as a Senior Big Data DevOps Engineer by leveraging your Kafka and AWS expertise in a hybrid role that offers significant impact and growth within a reputable company. You'll thrive here if you are passionate about optimizing enterprise-scale big data platforms and ensuring operational excellence. Apply now to contribute to innovative big data solutions and enhance your skills in a dynamic environment.

Quick Overview

Work Type
Hybrid
Level
Mid Senior

Job Description

Job Title: Senior Big Data DevOps Engineer (Kafka/AWS)

Location: Denver, CO or St. Louis, MO 

Duration : 12 Months

 
Job Summary 
Experienced Big Data Administrator responsible for managing, supporting, automating, and optimizing enterprise-scale Hadoop, Kafka, AWS cloud, and DevOps platforms. The role focuses on ensuring high availability, performance, security, scalability, and operational excellence across big data ecosystems while collaborating with development, architecture, and business teams. 

Key Responsibilities: 

Kafka Administration 

  • Deploy, configure, and manage Apache Kafka clusters and AWS MSK environments. 

  • Monitor broker health, partitions, replication factors, and consumer lag. 

  • Perform capacity planning and cluster scaling activities. 

  • Manage Kafka security using SSL, SASL, ACLs, and encryption standards. 

  • Troubleshoot producer, consumer, and broker performance issues. 

  • Support Kafka Connect, Schema Registry, Cruise Control, and MirrorMaker implementations. 

AWS Cloud Administration 

  • Manage cloud infrastructure services including EC2, S3, IAM, VPC, EBS, CloudWatch, CloudTrail and AWS Glue. 

  • Support AWS Managed Streaming for Kafka (MSK), EMR, Lambda, and Airflow environments. 

  • Implement cloud security best practices and governance controls. 

  • Perform infrastructure provisioning and automation using Infrastructure as Code (IaC). 

  • Monitor cloud resource utilization and optimize operational costs. 

DevOps & Automation 

  • Design and maintain CI/CD pipelines using Jenkins, GitHub Actions, GitLab CI, or similar tools. 

  • Automate infrastructure deployment using Terraform, CloudFormation, and Ansible. 

  • Manage source control repositories and release processes. 

  • Implement monitoring and alerting solutions using Prometheus, Grafana, Splunk, ELK, or CloudWatch. 

  • Support containerization technologies such as Docker and Kubernetes. 

  • Develop automation scripts using Python, Shell, or Bash. 

Operations & Support 

  • Provide Level 2 and Level 3 production support. 

  • Participate in on-call support rotations and incident management activities. 

  • Perform root cause analysis (RCA) and implement preventive measures. 

  • Create and maintain operational documentation and standard operating procedures. 

  • Ensure compliance with security, audit, and regulatory requirements. 

Required Skills 

  • Apache Kafka Administration 

  • AWS Cloud Services 

  • Linux (RHEL/Rocky Linux) 

  • Shell Scripting and Python 

  • Jenkins, Git, Ansible, Terraform 

  • Docker and Kubernetes 

  • Monitoring Tools (Grafana, Prometheus, Splunk) 

  • Networking, Security, and High Availability Concepts 

  • Performance Tuning and Capacity Planning 

Preferred Qualifications 

  • Bachelor’s degree in Computer Science, Information Technology, or related field. 

  • Experience with Cloudera CDP, AWS MSK, Airflow, and Spark. 

  • AWS, Google Cloud Platform, Kafka, or Kubernetes certifications. 

  • Experience supporting large-scale production environments handling petabyte-scale data workloads. 

Key Achievements Expected 

  • Maintain platform availability above 99.9%. 

  • Adopt AI-assisted engineering practices to improve operational efficiency, reduce manual effort, and accelerate troubleshooting and documentation. 

  • Automate repetitive operational tasks. 

  • Improve cluster performance and resource utilization. 

  • Ensure secure, scalable, and reliable data platform operations. 

  • Support enterprise data engineering, analytics, and AI/ML workloads efficiently. 

  

 

Skills

Docker
Shell
AWS
ELK
Encryption
Splunk
Airflow
Ansible
Apache
Bash
CloudFormation
Git
GitHub Actions
GitLab CI
Google Cloud
Grafana
Hadoop
Jenkins
Kafka
Kubernetes
Prometheus
Python
Terraform

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