How much does a data warehouse cost to build?

Senior nearshore rates run 30-50% below equivalent US salaries and consultancy fees. The build depends on how many sources feed it, how much modelling the business logic needs, and whether you are migrating from something. You get a line-item estimate on the first call, separate from the platform bill, which is yours directly from the vendor.

And what will it cost to run every month?

That depends on the model more than the platform. Cloud warehouses bill by compute, so a query that scans a whole table because the model was never partitioned costs many times one that does not. We size it during the assessment, set up cost monitoring from the first load, and report it monthly rather than leaving you to find it on the invoice.

Do we need a warehouse or a data lake?

If your sources are mostly tabular and the point is reporting, a warehouse. If you need to keep raw data for machine learning or you do not yet know what you will need, a lake or a lakehouse. Most companies that ask us for a lake need a warehouse, and starting with the lake usually means paying to store data nobody ever queries.

Snowflake, BigQuery, Databricks or Redshift?

Usually whichever cloud you are already committed to, unless a specific workload argues otherwise. We come in without a reseller incentive, so the recommendation follows your data, your team's existing skills and your commitments rather than our margin.

Can you modernize the warehouse we already have?

Yes, and it is a common way we start. We map what is actually running against what is documented, find the models and jobs nothing depends on any more, and re-model the parts that are costing you performance or money. Rebuilding from scratch is rarely the right answer.

How long before we see anything?

The first subject area in production typically lands within the first months, not at the end of the project. We deliver one area at a time, reconciled against the source, so the business gets something usable before the last table is built.

What happens to reporting during a migration?

The old warehouse keeps running and reporting in parallel until you confirm the numbers agree on the other side. Nothing gets switched off on a date we chose.

Who owns the warehouse and the models?

You do. The platform account, the repository and the dbt project are yours from the first commit, and the contract assigns all intellectual property to you. If the engagement ends, your team keeps building the next morning.

Can you work with our analysts and our BI team?

Yes, and it works better that way. Your analysts know what the numbers mean, which is the part no external team can supply. We build the model with them and hand over documentation they can read rather than a black box.

How do you handle sensitive data in the warehouse?

Column-level restrictions and masking for the fields that need it, role-based access modelled against how your organization is actually structured, and encryption in transit and at rest. For HIPAA, PCI DSS and SOC 2 we keep the evidence as we go rather than reconstructing it at audit time.

How fast can data engineers start?

We present matched profiles within days, you interview and approve them, and most engineers onboard in under 2 weeks.

How much time zone overlap will we have?

Our engineers work across Latin America on US Central and Eastern time, which gives 6-8 hours of daily overlap. Modelling work depends on it more than most, because half of it is asking your team what a field is supposed to mean.