Databricks Consulting & Lakehouse Implementation
Lakehouse architecture, Unity Catalog, and Spark pipelines built for production.
We design, build, and tune Databricks lakehouses. That covers the whole path: landing raw data, building bronze/silver/gold layers on Delta Lake, governing it in Unity Catalog, and serving it to BI tools and ML workloads.
Most teams we meet already have Databricks. The problem is not the platform — it is unclustered tables, oversized all-purpose compute, no CI/CD, and no clear ownership. We fix the engineering, then hand it back with runbooks so your team can run it.
What we do
- Lakehouse and medallion architecture on Delta Lake
- Unity Catalog: catalogs, governance, lineage, and row/column security
- Spark and Delta Live Tables pipeline development
- Migration from Hadoop, legacy ETL, or a standalone warehouse
- DBU and cluster cost optimization, photon and job-compute tuning
- Databricks Asset Bundles, CI/CD, and environment promotion
- Databricks SQL warehouses and BI serving layer
What you get
- A production lakehouse with documented bronze/silver/gold layers
- Unity Catalog governance model and access policies
- CI/CD pipelines and environment promotion via Asset Bundles
- A cost baseline with tuning actions and measured savings
- Runbooks and knowledge transfer for your team
How we work
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01
Assess
Review your workspace, workloads, cost, and governance gaps.
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02
Design
Define the target lakehouse architecture and delivery plan.
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03
Build
Implement pipelines, governance, and CI/CD in reviewable increments.
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04
Tune
Optimize compute and queries, then hand over with runbooks.
A low-risk way to start
Short, fixed scope, clear deliverable. You get a plan you can act on — with us or without us.
Databricks Assessment
An architecture, governance, and cost review of your Databricks workspace, ending in a prioritized action plan you can execute with or without us.
- Lakehouse architecture and Unity Catalog review
- DBU cost baseline with tuning actions
- Prioritized roadmap with effort and impact
Related work
Platforms we have built in this space, with the team setup and the architecture behind each one.
Frequently asked questions
Do you work with an existing Databricks workspace or only greenfield?
Both. Most of our work is on existing workspaces — fixing pipeline reliability, adding Unity Catalog governance, and cutting DBU spend. Greenfield builds are also common when a client is moving off a legacy warehouse.
Can you reduce our Databricks bill?
Usually yes. The common causes are all-purpose clusters used for scheduled jobs, oversized drivers, no auto-termination, unoptimized Delta tables, and full refreshes where incremental would do. We start with a cost baseline so savings are measurable.
Which clouds do you support?
Databricks on AWS, Azure, and Google Cloud. We work with the surrounding services too — S3/ADLS/GCS, IAM, networking, and the orchestration layer.
How do engagements usually start?
With a fixed-scope assessment. It gives you an architecture review, a cost baseline, and a prioritized action plan before you commit to a build.
Ready to talk about Databricks Consulting?
Tell us what you are working on. We reply within one business day, and we will tell you plainly if we are not the right fit.