Google Cloud Platform Data Engineer

Job Description

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Quantico Solutions Limited is a dynamic IT and technology company based in London, England, specializing in transforming AI and automation strategies into tangible business value. With a focus on data transformation, AI infrastructure, cloud migration, and intelligent automation, we combine strategic insight with technical expertise to deliver solutions that enhance efficiency, governance, and user experience for our enterprise clients. We are currently seeking a Cloud Data Engineer to join our innovative team.

If you are passionate about driving impactful data solutions within a forward-thinking company, we encourage you to apply and contribute to our mission of delivering measurable business outcomes through cutting-edge technology.

Get your hands dirty with Google Cloud by building, configuring, and managing environments, covering everything from networking to storage and IAM Dive into the world of Kubernetes on GKE, ensuring clusters are stable, secure, and always fresh Transform infrastructure into code with Terraform magic Be the maestro of CI/CD pipelines in GitLab, orchestrating smooth deployments Set up monitoring, logging, and alerting systems so we catch hiccups before they become headaches Apply those government-grade security controls, like NCSC Cloud Security, to keep us compliant and secure Be our go-to problem solver, fixing issues across the platform and jumping into incident action when things go sideways Collaborate with architects and security pros to turn awesome designs into reality Keep our builds, configurations, and changes documented in clear and easy-to-follow ways You gotta be SC/DV Cleared—don't worry, we won't ask you to divulge your superhero identity Have a thing for cloud technologies? xwzovoh Whether it's Azure, AWS, or one of the other cloud flavors, we need your expertise!

Show us your Kubernetes magic and make those clusters dance Terraform your way through infrastructure—your code should be as solid as rock CI/CD pipelines in GitLab are your jam, so we expect you to groove through seamless deployments Containers should be your best buds, especially if GKE is part of your toolkit