Databricks consulting · Salt Lake City, UT
Databricks consulting for Salt Lake City companies
Founder-run fintech and software companies here usually have a Postgres that became the warehouse by accident and a BI tool pointed at it. Lakebase and Lakehouse Federation let that first step be small, with the application's own data federated into Unity Catalog before anything moves, and the SOC 2 evidence comes from the audit tables rather than a project.
Founded
2017, and still independent
Bench
115+ engineers, 80 Databricks-certified
Experience
Fifteen years average, per engineer
Serving
Salt Lake City, Provo, Lehi, Ogden
A substantial fintech and software base along the Wasatch Front, a large integrated health system beside it, and an unusually high share of companies still run by their founders. If that's you, you want the AI system in production and its operating cost known, without a transformation programme in front of it.
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.
The first enterprise deal brings the questionnaire
Plenty of software and fintech companies between Salt Lake City and Lehi are still run by their founders, and the first large customer usually arrives with a security questionnaire and a SOC 2 Type II requirement. A fintech partnering with one of Utah's industrial banks, chartered by the state's Department of Financial Institutions, gets a second list on top, because the bank's examiners expect it to oversee its vendors.
Most founders treat that as a compliance project for after the build, and they lose two quarters to it. We'd rather the platform produce its own evidence from day one. Access reviews come from the grant tables, change history from the deploy pipeline, and the audit log is written by the system, so the questionnaire turns into a document exercise and the Type II window opens on something already running.
Your stack gets read against the Trust Services Criteria your auditor will test, and we mark which controls the platform can evidence by itself. Single sign-on with role-based access goes in first, then a single pipeline for every production change, then log retention long enough to cover the observation period. The product roadmap keeps moving beside it.
Clients we have done this for
If your application database has quietly become your warehouse, read how TotalLoop moved. It started as a cloud-native platform on Azure with its own CRM and a sales dashboard, and later moved off Cosmos DB and SQL Server onto Databricks Lakebase, converted with TechFabric Airlift and cut over in reversible waves.
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 Salt Lake City
Data engineers in Lehi and Salt Lake
The Utah Data Engineering Meetup gathers on the third Wednesday of most months, alternating between Recursion in Salt Lake City and Vivint in Lehi, and recent evenings covered multi-agent analytics and how teams pick a data stack. SQL Server people have a room of their own. The Utah SQL Server Group, which merged the old Salt Lake and Utah County groups, meets on Monday afternoons at a county library in Midvale.
Those two rooms describe two different first months. A company whose reporting runs on SQL Server and Power BI starts somewhere else from one whose warehouse is a Postgres that grew into the job. For the Postgres case we usually begin with Lakehouse Federation reading the database where it already sits.
The Salt Lake City-Murray metro area. Utah: Salt Lake and Tooele counties.
Lighter shape: the city itself. Dot: downtown. County boundaries from the US Census Bureau, 2023.
Meetup · Monthly, usually the third Wednesday evening
Utah Data Engineering Meetup
Recent sessions on multi-agent analytics and choosing a data stack make this the evening where you'll hear what a local data team picked, and why.
Volunteer organisers, part of Forge Utah. Alternates between Recursion, Salt Lake City, and Vivint, Lehi.
User group · Monthly, usually a Monday afternoon
Utah SQL Server Group
If your reporting still runs on SQL Server, the people in this Midvale room know exactly which stored procedures will fight a move to the lakehouse.
Volunteer organisers. Ruth Vine Tyler Library, 8041 S Wood St, Midvale.
Meetup · Monthly, usually the last Tuesday evening
MLOps and AI Utah
Engineers here talk about getting models deployed and monitored, which is the half of a Databricks project that decides whether anyone uses it after launch.
Volunteer organisers. Pattern, 1441 W Innovation Way, Suite 500, Lehi.
University · Ongoing degree programme
BS in Data Science, Kahlert School of Computing, University of Utah
Graduates of the Kahlert School's data science degree are the analysts most Utah companies will hire next, so it's worth knowing what tools they arrive expecting.
Kahlert School of Computing, University of Utah. University of Utah, Salt Lake City.
User group · Every one to two months
Salt Lake City R Users Group
Plenty of University of Utah research still lives in R scripts, and this group shows how that work could run against governed tables instead of local files.
Volunteer organisers. Talks online; socials around Salt Lake City, such as Millcreek.
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 Salt Lake City: common questions
What would Databricks look like for a Salt Lake City biotech?
Like Recursion's, at a smaller scale, with images and results kept together. Recursion, on Rio Grande Street in Salt Lake City, says it runs up to 2 million experiments a week to build a 50+ petabyte dataset, which shows where a lab's data heads once screening scales.
We'd keep the raw image files in a Unity Catalog volume and write each plate's metadata and assay readings to Delta tables that point at those files, so scientists query both under one set of grants. The plate map is where we'd expect disagreement, so we'd fix its schema with your lab lead first.
How does Utah's privacy law change a Databricks setup in Salt Lake City?
If the law covers you, it decides where personal data gets tagged. The state's Consumer Privacy Act applies to companies with at least $25 million in annual revenue that also handle the data of 100,000 consumers a year, or 25,000 if more than half their revenue comes from selling it.
Covered consumers can ask for deletion and opt out of targeted advertising. We'd tag personal columns in Unity Catalog as tables land, write masking policies against the tags, and keep a deletion job that finds a person across every table carrying their key.
Tags don't follow data into a copy, so three years of untagged copies is slow to clean up.
What would Databricks do for a Salt Lake City distributor's inventory data?
Give you one inventory number that warehouse, sales and finance all trust. Trade, transportation and utilities is the largest sector in the Salt Lake City metro, at 163,100 jobs against 155,800 in professional and business services, in September 2026 (preliminary) according to the Bureau of Labor Statistics.
We'd bring the warehouse system, ERP and carrier feeds into Delta tables and define on-hand and in-transit once, as metric views in Unity Catalog. Planning models come second, once a pallet counted at the dock shows up as the same pallet in finance's numbers.
We are founder-run and our first big customer wants SOC 2.
Then the useful thing is a platform that already produces the evidence, so the questionnaire becomes a document exercise. We would rather get one system into production with the trail built in than run a compliance programme alongside a build.
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 Salt Lake City
What else we build for Salt Lake City companies.
AI Consulting & Development Company in Salt Lake City
Your AI pilot answers well in the demo, and nobody can yet say what it'll cost a month or whether this week's change made it better.
Software Development Company in Salt Lake City
Your product was built by a founding team moving fast, and now every change breaks something and the people who know why are busy selling.
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The same work, in other metros. The full list is here.
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