# Databricks consulting services > Every databricks page on techfabric.com, with what each one answers. Canonical: https://www.techfabric.com/databricks --- ## Pages - [Databricks consulting](https://www.techfabric.com/databricks/consulting): TechFabric is a Databricks partner with 80 Databricks-certified engineers. We migrate warehouses off Snowflake, Synapse and Teradata, design Unity Catalog governance that survives an audit, build Databricks Apps and Lakeflow pipelines, and put agents on AI Gateway that inherit catalogue permissions rather than routing around them. - [Hire Databricks engineers](https://www.techfabric.com/databricks/hire-engineers): TechFabric places engineers from an award-winning Databricks engineering team inside your team, working in your workspace and your repository. Eighty of our engineers hold Databricks certifications, averaging fifteen years of production experience. Hire one engineer for a roadmap your team already owns, or a working team with a lead who owns the outcome. - [Lakebase implementation](https://www.techfabric.com/databricks/lakebase): Lakebase is a fully managed serverless Postgres that Databricks runs inside the lakehouse, with compute separated from storage, database branching, point-in-time recovery and Unity Catalog governance over it. We design the schema, wire the sync to your lakehouse tables, and build the transactional application or the agent memory that runs on it. - [Unity Catalog consulting](https://www.techfabric.com/databricks/unity-catalog): We design and implement Unity Catalog: catalogue and schema structure, grants that match how teams really work, migration off the Hive metastore, and lineage that survives a refactor. Built so applications and agents inherit those permissions rather than routing around them with a shared service account. - [Databricks cost optimization](https://www.techfabric.com/databricks/cost-optimization): We find the Databricks spend that is not buying anything: all-purpose compute running jobs that should be serverless, clusters sized for a load that never arrived, schedules nobody owns, and warehouses left running overnight. You get findings ranked by severity with the estimated saving and the reasoning behind each one. ## Common questions ### We are already on Databricks and shipping is the hard part. Where do you fit? That is the engagement we are sharpest for. Usually it is the initiative that keeps slipping because your team is fully committed elsewhere: the app that never leaves the notebook, the agent nobody trusts in production, the Lakebase service that keeps getting deferred. We take ownership of that piece without pulling anyone off the current roadmap, and we work in your workspace so nothing has to be handed back later. ### What makes you different from a data consultancy? We are a software company that went deep on Databricks rather than a data practice that added application work later. Most partners stop at the pipeline and the dashboard. We build what comes after: the application on top, the durable API underneath, the agent that survives production. That is ordinary work here. ### How many Databricks-certified engineers does TechFabric have? Eighty, as things stand today, sitting inside a team of 115+ across Phoenix, Amsterdam, Dnipro and Hyderabad. Certification only proves the floor. What matters more is that the same engineers have shipped production software for fifteen years on average. ### Do we have to already be on Databricks to work with you? No. Some engagements start before the first workspace exists, some rescue a stalled pilot, and some are a migration off a warehouse that has stopped paying for itself. Databricks is where we go deepest and it is what we lead with, and it is not a condition of working with us. We also build on Azure, AWS, GCP and Cloudflare. ### Which Databricks surfaces do you work with? Unity Catalog, Lakeflow, Delta, Databricks SQL, Databricks Apps, Model Serving, AI Gateway, Genie, Lakebase and Asset Bundles. Our accelerators are built on those same surfaces, so what we recommend is what we run.