Job Openings Devops Engineer

About the job Devops Engineer

Location: San Antonio

Devops Engineer

Tools & Technologies:

  • Apache Kafka (Self-managed or MSK)
  • AWS managed Apache Flink
  • Amazon EC2, S3, RDS, and VPC
  • Terraform/CloudFormation
  • Docker, Kubernetes (EKS)
  • Elk, CloudWatch
  • Python, Bash

Skills and Expertise:

  1. AWS Managed Services:
    • Proficiency in AWS services such as Amazon MSK (Managed Streaming for Kafka), Amazon Kinesis, AWS Lambda, Amazon S3, Amazon EC2, Amazon RDS, Amazon VPC, and AWS IAM.
    • Ability to manage infrastructure as code with AWS CloudFormation or Terraform.
  1. Apache Flink:
    • Understanding of Apache Flink for real-time stream processing and batch data processing.
    • Familiarity with Flinks integration with Kafka, or other messaging services.
    • Experience in managing Flink clusters on AWS (using EC2, EKS, or managed services).
  1. Kafka Broker (Apache Kafka):
    • Deep knowledge of Kafka architecture, including brokers, topics, partitions, producers, consumers, and zookeeper.
    • Proficiency with Kafka management, monitoring, scaling, and optimization.
    • Hands-on experience with Amazon MSK (Managed Streaming for Kafka) or self-managed Kafka clusters on EC2.
  1. DevOps & Automation:
    • Strong experience in automating deployments and infrastructure provisioning.
    • Familiarity with CI/CD pipelines using tools like Jenkins, GitLab, GitHub Actions, CircleCI, etc.
    • Experience with Docker and Kubernetes, especially for containerizing and orchestrating applications in cloud environments.
  1. Programming & Scripting:
    • Strong scripting skills in Python, Bash, or Go for automation tasks.
    • Ability to write and maintain code for integrating data pipelines with Kafka, Flink, and other data sources.
  1. Monitoring & Performance Tuning:
    • Knowledge of CloudWatch, Prometheus, Grafana, or similar monitoring tools to observe Kafka, Flink, and AWS service health.
    • Expertise in optimizing real-time data pipelines for scalability, fault tolerance, and performance.

Responsibilities:

  1. Infrastructure Design & Implementation:
    • Design and deploy scalable and fault-tolerant real-time data processing pipelines using Apache Flink and Kafka on AWS.
    • Build highly available, resilient infrastructure for data streaming, including Kafka brokers and Flink clusters.
  1. Platform Management:
    • Manage and optimize the performance and scaling of Kafka clusters (using MSK or self-managed).
    • Configure, monitor, and troubleshoot Flink jobs on AWS infrastructure.
    • Oversee the deployment of data processing workloads, ensuring low-latency, high-throughput processing.
  1. Automation & CI/CD:
    • Automate infrastructure provisioning, deployment, and monitoring using Terraform, CloudFormation, or other tools.
    • Integrate new applications and services into CI/CD pipelines for real-time processing.
  1. Collaboration with Data Engineering Teams:
    • Work closely with Data Engineers, Data Scientists, and DevOps teams to ensure smooth integration of data systems and services.
    • Ensure the data platforms scalability and performance meet the needs of real-time applications.
  1. Security and Compliance:
    • Implement proper security mechanisms for Kafka and Flink clusters (e.g., encryption, access control, VPC configurations).
    • Ensure compliance with organizational and regulatory standards, such as GDPR or HIPAA, where necessary.
  1. Optimization & Troubleshooting:
    • Optimize Kafka and Flink deployments for performance, latency, and resource utilization.
    • Troubleshoot issues related to Kafka message delivery, Flink job failures, or AWS service outages.

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