Negotiable
Undetermined
Remote
Remote
Summary: The role of DevOps Engineer is a remote position requiring extensive experience in infrastructure engineering, particularly with data engineering and pipelines. The candidate will be responsible for deploying and managing applications using various technologies, including Linux, Docker, and Kubernetes. The position is contract-based, lasting between 6 to 12 months, and seeks a highly skilled individual with a strong background in cloud platforms and CI/CD practices.
Key Responsibilities:
- Manage and deploy infrastructure solutions with a focus on data engineering and data pipelines.
- Utilize Linux systems and Docker for application deployments.
- Implement and maintain Kubernetes in production environments.
- Develop and optimize data architectures using Python and RDBMS.
- Work with streaming/messaging systems like Kafka and RabbitMQ.
- Utilize log processing and monitoring tools such as Logstash and Grok.
- Build and maintain CI/CD pipelines using GitHub and GitHub Actions.
- Operate within Google Cloud Platform for infrastructure management.
Key Skills:
- 10+ years of experience in infrastructure engineering.
- Strong experience with Linux systems and Docker.
- Hands-on experience with Kubernetes.
- Proficiency in Python and knowledge of RDBMS and data lakehouse architectures.
- Experience with Kafka and RabbitMQ.
- Expertise in log processing tools like Logstash and Grok.
- Experience with CI/CD pipelines using GitHub.
- Solid experience with Google Cloud Platform.
Salary (Rate): undetermined
City: undetermined
Country: undetermined
Working Arrangements: remote
IR35 Status: undetermined
Seniority Level: undetermined
Industry: IT
We have an opening for DevOps Engineer with Remote. Kindly Apply your updated resume if you are interested. Please find the job details below:
Position: DevOps Engineer
Location: Remote
Duration: 6 to 12 Months Contract Position
Required Qualifications
- 10+ years of experience in infrastructure engineering with exposure to data engineering and data pipelines
- Strong experience with Linux systems and Docker-based deployments
- Hands-on experience with Kubernetes in production environments
- Proficiency with Python and working knowledge of RDBMS and data lakehouse architectures
- Experience with streaming/messaging systems such as Kafka and RabbitMQ
- Expertise in log processing and monitoring tools including Logstash and Grok
- Experience building CI/CD pipelines using GitHub and GitHub Actions
- Solid experience working within Google Cloud Platform (Google Cloud Platform)