Senior DevOps Engineer with GCP

Remote.Bulgaria
Remote.Georgia
Remote.Kazakhstan
Remote.Poland
Алмати
Астана
Белград
Варна
Варшава
Вроцлав
Днепър
Ереван
Киев
Клуж-Напока
Краков
Ларнака
Лвов
Лодз
Люблин
Одеса
Рига
София
Тбилиси
Харков

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Position overview

We are looking for a Senior DevOps Engineer with strong Google Cloud Platform experience to support the migration of production workloads from AWS to GCP. In this role, you will work closely with development and platform teams to design, implement, and operate scalable and reliable cloud infrastructure.

Technology stack

Google Cloud Platform, GKE, CloudSQL, Pub Sub, Terraform, Kubernetes, Helm, CI CD pipelines, AWS, EKS, RDS, SQS, IAM, Apigee, BigQuery

Responsibilities

Design, implement, and manage cloud infrastructure on Google Cloud Platform using Terraform
Plan and execute the end to end migration of workloads from AWS to GCP, including compute, networking, storage, and managed services
Deploy, configure, and operate Kubernetes clusters on GKE with a focus on availability, scalability, and security
Manage and optimize GCP native services such as CloudSQL and Pub Sub
Define and maintain infrastructure as code standards, including module structure, state management, and CI CD integration
Collaborate with development and platform teams during architecture reviews, capacity planning, and incident response activities

Requirements

Hands on experience running Kubernetes in production environments, including workload management, networking, RBAC, and Helm
Practical experience with Google Cloud Platform services, especially GKE, CloudSQL, and Pub Sub
Experience participating in or delivering cloud migration projects
Strong working knowledge of Terraform for infrastructure provisioning and lifecycle management
Experience collaborating with development teams to support cloud based applications

Nice to have

Prior experience with AWS (EKS, RDS, SQS, IAM, or similar)
Familiarity with Apigee API gateway management and configuration
Experience with BigQuery for data warehousing and analytics workloads
Background in data migrations

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