Onsite Role (Need to be onsite for 4 days in week)

Virtual Interviews

Position: DevOps Engineer with K8s

Location: Santa Clara, CA (MUST BE LOCAL)

Duration: 12 Months with possible extension

MUST HAVE`s:

• In-depth knowledge in K8s administration (on Prem or cloud) on any platform
• Knowledge in setting and maintaining python environment and basics of ML model deployment
• Good knowledge of DevOps tool and how they interact with the software development and administration of those tools

JD Summary:

• Skilled engineer to join our team and contribute to the successful implementation and management of our cloud-based infrastructure.
• Stay up to date with the latest trends and advancements in Python, API, Web server administration, application server administration and Machine Learning technologies.
• The ideal candidate will have expertise in Cloud Kubernetes/OpenShift, application lifecycle management, experience with Cloud Kubernetes clusters, and a strong background in CICD implementation, architecture design, containerization, Docker and AWS.

Detailed JD:

• Know the installation and configuration of Python of all the latest version, the knowhows of a python upgrade, maintaining python environments.
• Knowledge in storage management of unstructured date.
• Good understanding of on-prem (NAS) and cloud storage technologies (FSX, Snap-Mirror, S3).
• Administer and maintain Python based API`s, Web servers, and application servers to ensure optimal performance and availability.
• Monitor and troubleshoot system issues, including performance bottlenecks, server crashes, and connectivity problems.
• Collaborate with development teams to ensure the seamless integration of API`s and Web services into existing systems.
• Implement security measure and best practices to protect API`s and servers from unauthorized access and potential threats.
• Manage and maintain Machine Learning infrastructure, including the deployment and monitoring of models, data pipelines and other ML components.
• Administer and maintain the Databricks platform, including cluster management, user access and security configuration.
• Monitor and troubleshoot issues related to Databricks clusters, job scheduling, data pipelines and data processing workflows.
• Collaborate with data engineers and data scientists to optimize and tune Databricks performance, ensuring efficient data processing and analytics.
• Work closely with IT Operations teams to ensure seamless integration of Databricks with other data storage systems, data lakes, and data warehouses.
• Automate and streamline Databricks administration tasks using scripting and automation tools.
• Manage the entire lifecycle of applications running on Cloud Kubernetes/OpenShift platforms.
• Monitor and troubleshoot application issues, perform upgrades, and ensure high availability.
• Design, deploy and maintain Kubernetes clusters on Cloud platforms such as AWS.
• Deploy and manage applications on AWS using services like EC2, S3, RDS, etc.
• Ensure scalability, security, and optimal performance of the Kubernetes infrastructure.
• Implement Continuous Integration and Continuous Deployment (CICD) pipelines for application releases.
• Configure and maintain CICD tools and frameworks such as Jenkins, GitLab CICD or similar.