GCP Java Developer

Company:  Resource Logistics, Inc.
Location: San Francisco
Closing Date: 01/12/2024
Hours: Full Time
Type: Permanent
Job Requirements / Description


Develop, deploy, refactor and manage spring boot APIs in GCP , GKE microservice environment ensuring they meet performance, scalability, and security requirements.

Participating in design discussions focused on scalability, design, and implementation best practices.

Working with other engineers and Clienthitects on breaking-down, scoping, and estimating tasks.

Implement GCP security best practices, including Identity and Access Management (IAM), VPC security, and data encryption using Cloud KMS.

Supporting teams on the use of cloud platform including providing guidance on design patterns, best practices, and security considerations.

Utilize Infrastructure as Code (IaC) to automate the deployment and management of GCP resources like GKE, Service Mesh, API gateway.

Design and implement CI/CD pipelines to streamline application deployment and updates

Collaborate with development, DevOps, and security teams to integrate and manage cloud services efficiently.

Identify, troubleshoot, and resolve technical issues related to GCP infrastructure, networking, and deployments.

Required Skills

GCP Expertise: Strong knowledge and experience in configuring and managing of Google Cloud Platform services, including Compute Engine, Cloud Storage, Pub/Sub, Cloud Functions, Apigee Gateway, service mesh and GKE.

API Expertise - Strong experience in developing RESTful APIs using spring boot

API Management: Hands on Experience in using Apigee Gateway for API design, security, and traffic management.

Database Management: Experience with PostgreSQL or GCP's AlloyDB.

Service Mesh Experience: Hands-on experience with service mesh technologies (e.g., Istio) for managing microservices communication and traffic routing.

CI/CD Pipeline Management: Experience with CI/CD tools like Jenkins, GitLab CI, or Cloud Build for automating deployments.

Containerization: Proficiency in containerization and orchestration tools such as Docker and Kubernetes.

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