Databricks data platforms & data quality

Data platforms that hold up under audit.

QualityLake designs, builds and governs Databricks lakehouses for European enterprises — with data quality, cost control and CI/CD built in from the first commit, not retrofitted after the first incident.

  • Unity Catalog governance
  • Terraform & Asset Bundles
  • SAP ERP integration
  • Streaming & batch
BRONZERAWSILVERCONFORMEDGOLDCERTIFIEDQUALITY GATEQUALITY GATEQUARANTINED
  • 6 years building on Databricks
  • 20+ years in data engineering
  • 5 active Databricks & Azure certifications
  • 3 SAP ERP integration programmes

Why this keeps happening

Most lakehouse problems are not platform problems.

The technology is rarely the constraint. The failures we are called in to fix are almost always design decisions that were deferred.

Quality found in the dashboard, not the pipeline

Bad records are discovered by the people who trusted them. Validation belongs at the boundary, with contracts and gates that fail loudly.

Governance bolted on after go-live

Permissions accumulate by exception until nobody can say who can read what. A Unity Catalog model in code, versioned like everything else, is the fix.

Costs that only surface at the invoice

Cluster sprawl, all-purpose compute for scheduled jobs, and no ownership tags. Cost design is an architecture decision, not a finance problem.

How we work

Fixed scope, defined deliverables, no open-ended time and materials.

Every stage has an end state you can point at. If the scope changes, we write a new one rather than quietly extending the invoice.

  1. 01

    Assess

    Five days, fixed price. We read the code, the catalog and the bills, and hand back a scored report.

  2. 02

    Design

    Architecture, governance model and quality model, agreed in writing before anyone opens an editor.

  3. 03

    Build

    Fixed-scope increments. Everything in Git, CI/CD from day one, reviewed as it lands.

  4. 04

    Hand over or run

    Your team owns it, with documentation and onboarding. Or we keep quality on a retainer.

Engagements

Priced work, not a day-rate relationship.

All prices exclude VAT.

Recommended

Lakehouse health check

€7,500

5 days, fixed

Architecture, governance, data-quality and cost audit of an existing Databricks estate. Deliverable: a scored report and a prioritised remediation roadmap.

Most engagements start here.

Platform foundation

from €38,000

4–6 weeks

A Unity Catalog-governed workspace, medallion architecture, Terraform infrastructure, Databricks Asset Bundles, reusable CI/CD templates, and your first two production pipelines with quality gates.

SAP to lakehouse

from €55,000

6–8 weeks

Master and transactional SAP ERP data extracted, modelled and incrementally loaded into the lakehouse with a documented semantic layer.

Cost and performance tune-up

€14,000

2 weeks, fixed

Compute right-sizing, job and query optimisation, tagging and chargeback. Deliverable: a measured before-and-after.

Data quality as a service

from €4,500 / month

Ongoing

Quality rules, data contracts and freshness SLAs monitored on your own Databricks compute, with a named engineer and a monthly quality review.

Fixed-scope engagements with defined deliverables. Day-rate work is available for extensions to an existing engagement.

Start with five days.

A health check costs €7,500 and tells you exactly what is wrong, what it costs you, and what to fix first. If we are not the right people to fix it, the report is still yours.

Book a health check