Mateo
Full Stack Developer
ReactNode.jsPythonTypeScriptNext.jsMongoDBAWSAIAPIs
Shakers for companies
Work with a senior Google Cloud Engineer
A certified Google Cloud Engineer who builds where your company already works: BigQuery with the data that today lives in spreadsheets, Cloud Run with services that deploy themselves and Vertex AI when the model reaches production.
Senior tech talent for your Google estate, starting within days and without oversized migrations.
- Certified talent in AI and agent skills
- Meet up to 3 AI Builders in 72 h
- Flexible collaboration models
+600
European clients across different industries
Top 4%
We work with the top 4% of certified talent in our community
72 hours
Meet 3 certified candidates in under 72 h
4.7/5
Our clients' satisfaction on Trustpilot
The talent mix your company needs
At Shakers you will find AI Engineers, Google Cloud Engineer and specialists across Tech, Product and Data
Ana
DevOps Engineer
DockerCI/CDAWSAzureKubernetesTerraformAmazon Bedrock
Lucas
Backend Developer
Node.jsPythonJavaGoPHPMySQLMongoDBDocker
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Emma
Security Engineer
Burp SuiteOWASP ZAPMetasploitNmapNessusTrivySnyk
Google Cloud Engineer: what this role brings to your project
A Google Cloud Engineer builds and operates systems on Google Cloud: they structure data in BigQuery, deploy services on Cloud Run or GKE and connect Vertex AI models with the company's processes.
They are the natural door for whoever already lives in the Google ecosystem: the decision is not which cloud to pick, but how to make the one you already pay for earn its keep.
Google CloudBigQueryCloud RunGKEVertex AITerraformPub/SubDockerPythonSQLLookerCI/CD
One provider. One contract. Full traceability
How Shakers works for your company
Post your project
Tell us about the project, its scope, the expertise you need and when you want to get to work.
You get three options
We match your brief against certified talent and introduce the three AI Builders who fit best.
The last word is yours
Meet the three specialists and choose who you collaborate with; we handle the rest.
Why work with Shakers
The advantages of adding this profile with Shakers
Your data finally gets queried
BigQuery structured so the business can ask without depending on anyone: spreadsheets stop being the company database.
Services that deploy themselves
Cloud Run with its container and its revision: every version ships without ceremony and rolls back with one click if something breaks.
Models in production, not demos
Vertex AI serves the model where the data already lives: no parallel platform, no duplicated projects to reach production.
Infrastructure defined as code
Terraform where the project asks for it: every piece can be reproduced and audited. Nothing stays hand-built from the console.
The whole ecosystem connected
From Workspace to Looker: the tools your company already uses, talking to each other instead of coexisting in isolation.
Capacity without growing headcount
A Google Cloud Engineer by project, no hiring process: certified talent that joins with your project and permissions.
Do I need a Google Cloud Engineer or a Data Engineer?
If the problem is structuring and governing data in BigQuery, the Data Engineer. If it is several Google pieces working together (data, services, model), the Google Cloud Engineer. Full projects need both.
How much does a Google Cloud Engineer cost?
Scope sets it: which project pieces get built, what migrates and what operation remains. At Shakers the budget closes per project before kickoff.
Is Google Cloud worth it for a small company?
If the company already lives in Google (Workspace, Sheets, Looker Studio), continuity weighs: same accounts, another level. A Cloud Architect takes the serious decision; this role builds it.
What does a Google Cloud project need to start?
Access to the project with scoped permissions, the data or services that hurt and one scoping session. With that, the inventory and the plan land in days.
Can a Google Cloud Engineer work remotely?
Almost everything: the project and services live in the cloud. Only the odd local-hardware deployment asks for presence.
Is a Google Cloud Engineer the same as a cloud architect?
No. The architect decides the shape of the platform and its cost; the Google Cloud Engineer builds it inside the ecosystem. On small projects one person does both with agreed scope.
What gets delivered in the first weeks
The inventory of the project with what runs and what it costs, the first dataset in BigQuery the business can query and the Cloud Run service with its reproducible deployment.
The cloud of the Google ecosystem
1,213 active tech job ads in Spain mention Google Cloud, according to Shakers' market analysis (n=30,508, September 2026). One fifth of AWS: less market noise, more of a consultancy niche.
Where the Google Cloud Engineer ends
They do not set the multi-cloud strategy (Cloud Architect) nor build the full data pipeline (Data Engineer): they make Google's pieces work together. If your problem lives in the Google Cloud project, it is theirs.
A team by project, not a vacancy
The brief arrives with the project and the question: data nobody queries, a model unserved. Scope closes before kickoff and stays documented.
Connect with AI specialists to build your next project
Find specialists in Tech, Product, Data to complement your team
Cloud Architect
Decides the shape of the platform and whether Google is the cloud: the decisions your engineer builds inside the project afterwards.
Data Engineer
When the heart of the project is the data: pipelines, quality and BigQuery governance beyond the platform itself.
AWS Engineer
The same builder craft on the Amazon cloud: the page that comes in when the client's estate is AWS.
DevOps Engineer
The automation of the software's path: their pipeline deploys what your Google ecosystem holds up.
The AI talent you need Certified by Shakers
We introduce you to three ready_to_build AI Builders in 72 hours.
