Databricks consulting · Austin, TX
Databricks consulting for Austin companies
If you bought Snowflake or Synapse early, you may now be paying for a second stack to run AI beside it. Moving onto Databricks puts tables, models and agents behind one set of Unity Catalog grants, which your SOC 2 auditor wants to see, and makes the model bill forecastable. In Austin that's a SaaS company facing its first enterprise security review, or a chip-equipment maker or health-tech startup near Dell Medical School.
Founded
2017, and still independent
Bench
115+ engineers, 80 Databricks-certified
Experience
Fifteen years average, per engineer
Serving
Austin, Round Rock, Cedar Park, San Marcos
Semiconductors and software in roughly equal measure, a decade of corporate relocations, and a startup base that has grown into companies with real compliance obligations. If yours is one of them, you've probably shipped an AI feature already and now need it to be durable, measured and affordable.
AzureTechFabric is a Databricks partner with an award-winning Databricks engineering team, 80 of them Databricks-certified, and a Temporal partner. Where a system reaches past the workspace we build on Azure, AWS and Google Cloud.
Databricks Community Genie-Powered App Challenge, September 2026. Second place worldwide, judged and announced by Databricks.
What databricks consulting covers
Migration off Snowflake, Synapse and Teradata
Run through TechFabric Airlift, with executable playbooks for twenty-seven source platforms, signed migration certificates, and a cutover you can reverse at two in the morning.
Unity Catalog governance
Catalogue and schema design, a grant model expressed through groups, row filters and column masks, and lineage that survives a refactor. The boundary your agents and Power BI inherit.
Lakeflow pipelines
Ingestion and Lakeflow jobs with schema evolution handled rather than hoped for, medallion boundaries drawn on purpose, and jobs that recover instead of restarting from zero.
Databricks Apps and agents
Applications that run inside the workspace under their own service principal, and agents on Unity Gateway that inherit catalogue permissions instead of routing around them.
Genie and AI/BI
Metric definitions agreed with the person who owns the number, and a benchmark suite Genie has to keep passing, so the answer holds up when finance checks it.
Cost that somebody can defend
Cluster policies, warehouse sizing, file layout and the queries that actually pay. Instrumented at build time rather than discovered on an invoice.
Compliance arrives before the security hire
Austin's software companies tend to meet their compliance obligations before they've hired anyone to own them. The first enterprise deal brings a security questionnaire and a SOC 2 request together, and the Texas Data Privacy and Security Act has covered the personal data of Texas residents since 1 July 2024. The state attorney general enforces it, and gives a company 30 days to cure a violation before suing.
Screenshots and a spreadsheet of who approved what get most companies through their first audit, and the spreadsheet gets rebuilt the following year. We think evidence should come from the platform as it runs. Every deploy, grant and read of customer data gets recorded when it happens, so the platform already holds whatever sample the auditor picks, and deciding that up front costs days where retrofitting it costs a quarter.
We list the controls your auditor will test and trace each one to the event that proves it, then wire those events before touching features. Model calls get the same treatment, with the prompt version and cost logged per request, because enterprise security questionnaires have started asking how AI features are governed.
Clients we have done this for
Like many software companies, TotalLoop began as a cloud-native platform on Azure with its own CRM and a sales dashboard. It later moved off Cosmos DB and SQL Server onto Databricks Lakebase, converted with TechFabric Airlift and cut over in reversible waves, the careful way to change a database under a live product.
B2B ecommerce
DealerIQ
TotalLoop finds a dealership's customers with equity in their vehicle and matches them to cars on the lot. DealerIQ brought the idea and the dealership know-how, and our senior engineers worked inside its team to build it on Azure, test it with one dealer account and ship a lean first version. Later we moved it off Cosmos DB and SQL Server onto Databricks Lakebase, in waves that could each be rolled back.
How an engagement runs
01
Two weeks, fixed fee
A Databricks Health Check reads the workspace and returns a scorecard: compute cost, job reliability and Unity Catalog gaps, with what to fix first. You keep the document either way.
02
Scope you can defend
For a migration, the two-week Migration Readiness Sprint inventories the estate, agrees exclusions and hands you a wave plan before anyone picks a date.
03
Build in your workspace
The work runs in your workspace and your repository, with your engineers in it from the first week, so the pattern is one they can extend.
04
Hand over with the reasoning
A written record of what was decided and why, which the next platform lead almost never gets.
Two weeks, fixed fee, and a written plan whether or not you build it with us.
Tell an engineer what you want to build
A senior engineer reads it and replies within one business day, usually with the questions that decide the first two weeks.
Around Austin
Austin's lakehouse crowd
The Austin Databricks User Group meets every few months in person, with sessions on platform updates and Summit recaps, and this year it ran a DevConnect evening on Lakebase, Genie and MLflow. MLOps World, now in its seventh edition, brings its GenAI Summit to the Etter-Harbin Alumni Center by the UT stadium for two days of case studies on getting models and agents into production.
The Austin user group's DevConnect night put Lakebase, Genie and MLflow on one agenda, which amounts to running apps, questions and models on the same platform as the tables. For a SaaS company facing its first SOC 2 audit, that consolidation is the argument that matters, since one set of Unity Catalog grants is far easier evidence than two stacks. MLOps World's case studies are where you'll hear what broke on the way.
The Austin-Round Rock-San Marcos metro area. Texas: Bastrop, Caldwell, Hays, Travis and Williamson counties.
Lighter shape: the city itself. Dot: downtown. County boundaries from the US Census Bureau, 2023.
User group · Every few months, in person
Austin Databricks User Group
Its DevConnect night put Lakebase, Genie and MLflow on one agenda, which is exactly the consolidation question a SaaS company faces before its first audit.
Qubika, for the Databricks User Groups community. Austin, venue announced to registrants.
Conference · 17 to 18 November 2026 in person, 16 November online
MLOps World and GenAI Summit 2026
Workshops on model serving and evaluation show what a lakehouse has to provide once machine learning is running in production rather than in notebooks.
TMLS, with a volunteer steering committee. Etter-Harbin Alumni Center, Austin, TX.
University · Ten months full-time, or 23 months part-time
MS in Business Analytics and Artificial Intelligence, McCombs School of Business, UT Austin
Hiring analysts who already think in predictive models? This programme, part-time or full-time, is the closest local source.
McCombs School of Business, The University of Texas at Austin. UT Austin campus; part-time online with five Austin visits.
Conference · Once a year, recently in May or June
SQL Saturday Austin
A free Saturday at Microsoft's Stonelake Boulevard office where Austin's SQL Server and Power BI people compare notes, the right room for a team deciding whether its next warehouse is a lakehouse.
Austin SQL Server User Group, part of the PASS community. Microsoft, 10900 Stonelake Blvd, North Austin.
Each listing was checked on its organiser's own page on 12 October 2026. Dates and venues move, so the link is the source.
FAQ
Databricks consulting in Austin: common questions
Where do Austin teams compare notes on running Databricks?
At the Austin Databricks User Group, which holds in-person evenings for teams on the platform. Its sessions have included a Data + AI Summit recap and a night of Databricks updates and networking, which makes it a good place to hear what other Austin companies run into.
Our own group is the Gilbert Databricks User Group, which meets at our office in Gilbert, Arizona. For a project we'd fly in for discovery and the opening weeks of the build.
Can our Austin B2B SaaS product serve customer-facing analytics from Databricks?
It can, and the tenancy model is the part to get right first. Professional and business services is the Austin metro's largest sector, at 291,200 jobs against 214,100 in trade, transportation and utilities, according to the Bureau of Labor Statistics (September 2026, preliminary).
If firms like those are your customers, we'd expect them to want their numbers inside your product. We'd put a row filter keyed to the tenant on every shared table in Unity Catalog, serve the embedded dashboards from a SQL warehouse sized for your traffic, and test that one customer's login sees nothing of another's before any feature ships.
Our Austin lender's risk models live on laptops. Where would Databricks start?
With the inventory. Financial activities accounts for 93,000 jobs in the Austin metro, per the Bureau of Labor Statistics (September 2026, preliminary). Before moving anything at a lender, we'd find out which models feed real decisions and whose laptop or notebook each one lives in.
Then we'd register each model in Unity Catalog with its training table and version logged through MLflow, so a validator can see which data produced which score. Moving them into scheduled jobs comes after that, starting with the model your examiners ask about most.
We need SOC 2 and our first enterprise security review at once.
A platform that already records who did what, under whose authority and when, turns both from a project into a document exercise. The work is deciding where evidence comes from before the first handler is written, which costs almost nothing then and a quarter afterwards.
Learn Databricks first, free
The engineers who do this work wrote a free manual for the platform, from the account up, with a guided first hour on Free Edition. Most teams have somebody who needs it before anybody needs us.
How to learn Databricks
A path from zero to production: what to read, what to build, which certification is worth sitting, and in what order.
Getting started on Free Edition
From a free account to a governed table, a dashboard, a Genie answer and a small agent, in about an hour and at no cost.
Gilbert Databricks User Group
The meetup we organise, with recordings of past sessions.
Also in Austin
What else we build for Austin companies.
AI Consulting & Development Company in Austin
You shipped an AI feature to win the first enterprise deal, and now it has to hold up in production without engineers babysitting it.
Software Development Company in Austin
The platform your business runs on was written for a company half your size, and the people who wrote it have moved on.
App Development Company in Austin
Your app shipped fast and won real users, and now every release breaks something nobody still on the team wrote, so the launch you promised keeps sliding.
Databricks consulting elsewhere
The same work, in other metros. The full list is here.
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