Hire senior Google Cloud engineers through Probegin — GKE, BigQuery and the data-and-AI cloud, staffed nearshore. Profiles within days, start within two weeks, 60-day trial.
Container platforms on the cloud that runs Kubernetes best — with autoscaling and cost discipline built in.
BigQuery, Dataflow and Pub/Sub estates — where GCP placements most often earn their keep.
Vertex AI pipelines and model-serving setups for teams productionizing ML and LLM workloads.
GCP alongside AWS/Azure where acquisitions or tooling made it so — pragmatism over purity.
GCP earns the choice when data and Kubernetes lead. It pairs tightly with our data engineering and AI benches — often the same engagement.
Analytics estates where the warehouse is the product.
Teams that chose the cloud that runs Kubernetes best.
Serving and monitoring ML/LLM workloads in production.
Senior specialists; the GCP bench overlaps heavily with our data engineering and AI-native talent, reflecting what GCP is chosen for.
Building AI into this stack? Meet our Engenheiro de dados profile.
One specialist, embedded in your team, your standups and your tools — the classic direct model. Most placements run this way for a year or longer.
Two or three days a week for maintenance-grade or advisory work — you keep senior capability without paying for idle hours.
For outcome-scoped delivery, the specialist joins one of our implementation pods — priced on the result, not the hours.
Cloud and platform rates reflect production responsibility: an engineer holding your uptime prices above one writing pipelines. As a public anchor, Dutch IT detachering averages about €65–150 per hour (ITRC, 2026); direct nearshore hiring typically beats comparable local seniority on total cost because nothing is stacked in between. All-in rates are quoted per candidate in the intro call.
A 30-minute intake: the role, the stack, the team it lands in, the timeline it has to hit.
Two to three vetted Google Cloud engineers from our 400K+ European network — within days.
És tu que conduzes as entrevistas e tomas a decisão. Sem pressão, não temos nenhum lugar a preencher.
Tratamos dos contratos e da integração. Um período experimental de 60 dias, pelo que o risco é todo nosso.
Your Google Cloud engineers work from our network across the Netherlands, Ukraine, Hungary, Romania, Poland and Bulgaria — all CET ±1, all fluent English (C1), all contracted and payrolled by Probegin so compliance stays our problem, not yours.
When BigQuery, GKE or Vertex AI are load-bearing — GCP's strengths are data and Kubernetes, and our bench reflects exactly that.
Yes — BigQuery modeling, Dataflow pipelines and Pub/Sub event estates are the most common GCP engagements, often paired with a data engineer.
Yes — model serving and ML pipelines on Vertex are on the bench, and for agentic products we pair with our AI engineers.
Profiles within days, start within two weeks, 60-day trial as standard.
Depends on what's load-bearing: BigQuery estates usually argue for staying; thin compute footprints migrate cheaply. You get that assessment in week one, with numbers.
The first 60 days are the proof: if the match isn't right, you say so and the placement ends without long-term obligation — or we replace the profile from the network. Most trials convert; the ones that don't cost you a conversation, not a contract.
Yes — that's the normal growth path. Many clients start with a single specialist and expand to two or five as the roadmap demands, keeping one contract and one point of contact at Probegin. Scaling down is equally simple, with reasonable notice instead of penalty clauses.
Probegin does. You get one Dutch counterparty and one invoice; employment, payroll and cross-border compliance for the specialist are our responsibility. That structure also keeps you clear of freelance-classification risk under Dutch rules.
Tell us the role today, meet your matches this week, have them on the team in two.
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