Lakehouse & data platform
We design and build your Lakehouse on Databricks: Unity Catalog governance, medallion architecture, and a single platform where engineering, analytics, and ML share one source of truth.
Databricks Consulting Partner
Databricks work, measured in outcomes.
Tarmac is a Databricks Consulting Partner, and we would rather show you a pipeline in production than a partner badge. We build Lakehouse platforms, engineer the pipelines, and ship ML and AI on Databricks, with senior teams that work in your time zone.
What we deliver
From Lakehouse to production ML
One senior team across data engineering, analytics, and machine learning, all on a single Databricks platform.
Data engineering pipelines
Reliable batch and streaming pipelines with Delta Live Tables and Spark, tested and observable, so data lands clean and on schedule instead of breaking in silence.
ML & AI on Databricks
Model training, MLflow tracking, feature stores, and deployment, plus GenAI and RAG on Mosaic AI. Production machine learning, not notebooks that never ship.
Migration to Lakehouse
Move off legacy warehouses, Hadoop, or a tangle of point tools onto Databricks, with a plan that keeps the business running while the platform changes underneath it.
Cost & performance tuning
Cluster right-sizing, job optimization, and Photon and autoscaling done right, so your Databricks bill reflects the work you need, not idle compute burning through credits.
Governance & reliability
Unity Catalog access control, lineage, and data quality checks wired in from the start, under the Tarmac 10 quality process, so the platform is trustworthy as it grows.
Why Tarmac
A partner sized to your problem, not to a leaderboard
We are a focused senior partner competing on results. Here is what that gets you versus a badge-first consultancy.
- 01
Outcomes over tiers
We do not sell you a badge. We are measured by the pipeline that runs, the model in production, and the bill that went down, not by a partner status page.
- 02
Senior teams only
Our engineers average 10 years of experience and work in your time zone. You get people who have shipped Databricks platforms before, accountable for every merge.
- 03
Right-sized and flexible
A focused senior team that scales up or down with the work. 6-month contracts with 30-day cancellation, so you are never locked into capacity you stopped needing.
- 04
Referral-led track record
85% of our new work comes from referrals, and we hold a 5.0 rating across verified Clutch reviews. Clients keep coming back because the outcomes hold up.
Questions, answered
Databricks consulting FAQ
Is Tarmac a Databricks partner?
Yes. Tarmac is a Databricks Consulting Partner. We build Lakehouse platforms, engineer pipelines, and ship ML and AI on Databricks. We lead with outcomes rather than partner-tier bragging: what matters is the platform running in production and the results it delivers.
Why choose a smaller Databricks partner over a large firm?
You get senior engineers on your project instead of a pyramid of juniors, direct access to the people doing the work, and pricing that reflects a focused team rather than a large consultancy’s overhead. We compete on results and long-term relationships, not headcount.
Can you migrate us to Databricks from our current stack?
Yes. We migrate teams off legacy warehouses, Hadoop, and scattered point tools onto a Databricks Lakehouse, with a phased plan that keeps the business running throughout. Migration usually pairs with a cost and architecture review so you are not carrying old waste onto the new platform.
Do you do both data engineering and machine learning on Databricks?
Yes, and that is the point of the Lakehouse: one platform for both. We build the pipelines and governed data foundation, then train, deploy, and monitor models on top of it with MLflow and Mosaic AI, so engineering and ML are not two disconnected efforts.
How does this relate to your other data and AI services?
Databricks is the platform many of our data and AI engagements run on. Our Data Engineering & Analytics team builds the foundation and pipelines, and our AI & Applied ML team builds the models and agents. This page is the Databricks-specific view of both.
Building on Databricks, or thinking about it?
Tell us what you are trying to ship. We will bring a senior team that turns Databricks into a platform that actually delivers, with results you can measure.