Databricks consulting · San Diego, CA
Databricks consulting for San Diego companies
Auditors keep asking for a result reproduced exactly, months later, from the data as it was, and your warehouse can only approximate it. We migrate that history onto Databricks, where Delta time travel and Unity Catalog lineage give the reproduction for CMMC and GxP alike. Biotech, defence and wireless research make San Diego the strictest case, and a hospital or a real estate firm gets the same reproducibility.
Founded
2017, and still independent
Bench
115+ engineers, 80 Databricks-certified
Experience
Fifteen years average, per engineer
Serving
San Diego, La Jolla, Carlsbad, Chula Vista
Biotechnology, defence contracting and wireless telecommunications, three industries with long development cycles and no tolerance for an unexplainable result. If you're in one of them, a model that informs a decision has to show what it read, and evaluation has to produce a number someone can defend.
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.
Defence and biotech ask for the same replay
San Diego builds for two kinds of reviewer. Contractors supporting NAVWAR and the Navy commands around San Diego Bay now find CMMC requirements written into Defense Department contracts, and the labs on Torrey Pines Mesa answer to the FDA's 21 CFR Part 11 for electronic records. Both want access controlled and a result that can be reproduced from the records as they stood at the time.
The usual answer is a snapshot taken at month end and a spreadsheet saying which version fed which report. Reviewers stop trusting that the first time a number moves. We'd make reproduction a property of the platform, with every table versioned and every result tied to the version it read, so rerunning last March's analysis gives last March's answer without relying on anyone's memory.
We start with one result somebody has already been asked to reproduce, trace it back through the pipeline, move those tables onto Delta with retention set to cover your review cycle, and record lineage in Unity Catalog. If the rerun matches, that path becomes the pattern for the rest, and if it doesn't, the mismatch shows the real scope.
Clients we have done this for
Synapse and SQL Server gave way to Databricks Lakehouse and Lakebase at Location Services, cut over in reversible waves, and the rules engine that validates a repossession assignment on arrival now runs against governed lakehouse data. Any team whose decisions run on rules over a SQL Server history will find its own migration in that sequence.
Automotive / Fintech
Location Services
Location Services' repossession platform automates assignment intake, so fewer people handle each case, and our engineers built it with the company's own technology team. When it was time to leave Synapse and SQL Server, we moved it onto Databricks in waves that could each be rolled back, and the rules engine that checks every assignment came through unchanged.
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 San Diego
Data science on the La Jolla mesa
UC San Diego's Halıcıoğlu Data Science Institute runs everything from undergraduate data science majors to a PhD, with an MS in Data Science and an online master's in between. Its Master of Advanced Studies in Data Science and Engineering is taught in person at weekends, for people who keep their jobs. Both sit on the La Jolla campus, a short drive from the biotech labs where much of the region's assay data starts.
Whether the data comes off a sequencer or a Navy test range off Point Loma, the hard part of the migration is reproducing a six-month-old result exactly from the warehouse it lives in now. Where that attempt breaks is the real scope of the job. Delta's time travel and Unity Catalog's lineage are what make the second attempt pass, and that's the part we'd build.
The San Diego-Chula Vista-Carlsbad metro area. California: San Diego County.
Lighter shape: the city itself. Dot: downtown. County boundaries from the US Census Bureau, 2023.
University · Ongoing degree programme
Master of Advanced Studies in Data Science and Engineering (MAS-DSE), UC San Diego
Weekend classes let working engineers take UC San Diego's data science and engineering master's, a way to grow a lakehouse team from inside.
UC San Diego Halıcıoğlu School of Data Science and Computing. UC San Diego, La Jolla.
Meetup · Weekly, Saturdays at noon
San Diego Machine Learning
Dataset engineering comes up often on these Saturdays in Rancho Bernardo, and it's the part of a migration that decides whether models can trust the tables.
Volunteer organisers. Aquillius, 10918 Technology Pl, Rancho Bernardo.
User group · Monthly, usually the fourth Thursday evening
San Diego Python Users Group
Held in Qualcomm's Building Q and streamed, the monthly speaker night draws the Python users whose notebooks a migration has to bring along.
Volunteer organisers, part of the Python Software Foundation network. Qualcomm Building Q, 6455 Lusk Blvd, Sorrento Mesa.
University · Ongoing
Halıcıoğlu Data Science Institute (HDSI), UC San Diego
From undergraduate majors to a PhD, HDSI is the nearest source of data scientists for the biotech labs and defence teams around La Jolla.
UC San Diego. UC San Diego, 9500 Gilman Dr, La Jolla.
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 San Diego: common questions
Do you work with San Diego companies?
Yes, and with companies across the United States. Arizona does not observe daylight saving, so from March to November we are on the same clock as you and from November to March we are an hour ahead. Either way the working day overlaps almost completely.
Do you have an office in San Diego?
The office is in Gilbert, Arizona, with teams in Amsterdam, Dnipro and Hyderabad. Delivery is remote or hybrid, and we travel for discovery, workshops and the opening weeks of a build.
We need results a reviewer can reproduce exactly.
Replay is how. The event log is the source of truth and read models derive from it, so reproducing a result means replaying to a point rather than trusting that a snapshot was taken. Defence and biotech both need that and neither accepts an approximation.
What makes you an award-winning Databricks engineering team?
In September 2026 Prove It, an app built by TechFabric engineer Ivan Vydrin, was named a winner in the Creativity & Originality track of the Databricks Community Genie-Powered App Challenge, placing second worldwide in a contest Databricks ran and judged. The announcement is on community.databricks.com and the code is public.
What level of Databricks partner are you?
TechFabric is a Databricks partner. We don't publish a tier, because tiers measure commercial relationship as much as engineering depth, and we would rather be judged on the bench and the work. Eighty of our engineers are certified, we run our own business on the stack, and the four accelerators we bring are open source.
Learn Databricks first, free
The engineers who do this work wrote a free manual for the platform, forty-three chapters 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 San Diego
What else we build for San Diego companies.
Databricks consulting elsewhere
The same work, in other metros. The full list is here.
New York, NY
New York, Brooklyn, Queens
Boston, MA
Boston, Cambridge, Somerville
Atlanta, GA
Atlanta, Alpharetta, Marietta
Miami, FL
Miami, Fort Lauderdale, Coral Gables
Charlotte, NC
Charlotte, Concord, Gastonia
Philadelphia, PA
Philadelphia, King of Prussia, Wilmington
Detroit, MI
Detroit, Ann Arbor, Dearborn
Tampa, FL
Tampa, St. Petersburg, Clearwater
Chicago, IL
Chicago, Naperville, Evanston
Phoenix · Dallas · Houston · Austin · Nashville · Minneapolis · Denver · Salt Lake City · Los Angeles · San Francisco · Seattle · Washington · Orlando · Raleigh · Portland