What are the responsibilities and job description for the Devops Engineer position at Mothership ?
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 :
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 . 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). 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. 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. 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. 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 :
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. 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. 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. 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. 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. 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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