BigQuery costs hard to explain?
Review how queries use data and identify avoidable processing.
CARLOS VERLIQUE · VERLIQUE TECHNOLOGIES
More efficient BigQuery.
More dependable pipelines.
I’m Carlos Verlique. I help teams investigate data costs, improve reliability, and modernize workflows on Google Cloud.
Where does your team need help?
Data updates need too much attention?
Improve incremental updates, validation, and recovery from failures.
Your pipeline needs to evolve?
Evaluate a practical path to modernization, with maintenance in mind.
ONE IDEA, MADE VISIBLE
The same report can take less repeated work.
Compare two ways to update a fictional sales report.
THE PERSON BEHIND THE WORK
Carlos Verlique
Data engineer · Verlique Technologies
My work combines Python, SQL, and Google Cloud with a practical approach: understand the problem, measure current behavior, implement, validate, and document. Cost, reliability, and your team’s ability to maintain the solution guide each decision.
Understand → Build → Validate & hand over
Tools and technical scope
Python, SQL, BigQuery, Cloud Run, Dataproc/Spark, Cloud Scheduler, Cloud Build, Cloud Storage and PostgreSQL. The workload determines the approach.
Datastream can be evaluated when planning change-data integrations, according to source compatibility and project needs.
What would you like to improve?
A short description is enough to start.