Data warehouse consulting — senior engineers, not consultancies

You’re either building a data warehouse from scratch or migrating away from something that stopped working. Either way, you need engineers who’ve done this before, not a consulting firm that sells you a methodology and delivers junior analysts.

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What these engineers build

Cloud data warehouses

Snowflake, BigQuery, Amazon Redshift, Databricks Lakehouse — the engineers work with all of them. Platform choice depends on your cloud provider, your query patterns, and what your downstream BI tools connect to well. If you haven’t chosen yet, they’ll tell you what fits your situation, not what’s on the consulting firm’s preferred vendor list.

Migrations from legacy systems

Oracle, SQL Server, Teradata, on-prem Hadoop clusters — the migration path to a cloud warehouse is well-understood if you have engineers who’ve done it. The work involves schema conversion, ETL rewriting, data validation, and a cutover plan that doesn’t shut down reporting for a week.

dbt modeling layers

The engineers build dbt models that sit between raw ingested data and the tables your analysts query. Staging models, intermediate transforms, final mart models, documentation, tests. A properly built dbt layer means your analysts are querying clean, tested, version-controlled data — not writing the same CTE in every SQL query.

Data marts

Purpose-built subsets of the warehouse for specific teams or use cases: finance mart, marketing mart, product analytics mart. Marts reduce query complexity and let you apply team-specific access controls without exposing raw tables.

Typical team

1–2 senior data engineers

One engineer can build a greenfield warehouse end to end. Two engineers run in parallel when you have both a complex migration and active new pipeline development at the same time.

Optional: data architect — for large-scale warehouse designs or organizations with multiple business units feeding into a single warehouse, a data architect provides the logical design and governance model before the engineers start building. This is usually a short engagement (2–4 weeks) that front-loads the decisions you don’t want to revisit after 3 months of build work.

Tech stack

Common use cases

Greenfield warehouse build — starting from scratch, often when a company has outgrown spreadsheets or a product database that analysts have been querying directly. The engineers scope the initial data model, set up ingestion from your source systems, and build the first marts.

Migration from on-prem to cloud — moving from an on-prem SQL Server or Oracle data warehouse to Snowflake or BigQuery. Involves schema migration, ETL/ELT rewriting, data validation against the source, and a phased cutover.

Consolidating multiple source systems — companies that have grown through acquisition often have 4–6 source systems feeding separate data silos. The engineers build the unified warehouse and define the canonical data model across systems.

How billing works

You pay by the hour, settled monthly. During a heavy migration sprint, you might run a 2-person team full time for 2–3 months. Once the warehouse is in steady state, you might step down to one engineer at 50% time handling ongoing pipeline maintenance and new source system integrations.

T&M billing means you don’t pay for time you don’t need. It also means you’re not negotiating a change order every time a new source system appears mid-project.

Engineers are employed through staffai.eu. You don’t deal with payroll, benefits, or local employment compliance in Romania or Bulgaria.

What this costs

Indicative monthly team cost for a senior data engineer:

€5,000 – €7,500/month per engineer, depending on seniority and specialization.

A 2-person team running a warehouse migration: €10,000 – €15,000/month.

Compare that to US or Western European data warehouse consulting: firms charge $200–$350/hour for senior data engineers, putting a 2-person team at $70,000–$120,000/month before any fixed-fee project overhead.

Related pages

• Hire data engineers
• Data engineering services
• Data lake architecture

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