One lakehouse for

Data & AI.

Brilworks pairs certified Databricks engineers with a data engineering practice built on real production work. We bring your data, analytics, and ML onto a single lakehouse, so the same governed data feeds your pipelines, your dashboards, and your models.

From there we build the Spark pipelines, Unity Catalog governance, and Delta architecture that move data from raw to production cleanly, then put ML and GenAI on top of a foundation solid enough to hold it. No silos between your warehouse and your data science, no copies drifting out of sync.

Why enterprises choose us

Why enterprises choose Brilworks for Databricks

Certified Databricks partner

Our engineers are Databricks-certified and have shipped Spark, Delta, and MLflow in production, not just trained on them. You get people who have done this before.

Built for scale

Databricks earns its keep on heavy workloads. We design Spark jobs and Delta tables that stay fast and predictable as data volume climbs into billions of rows.

Full lakehouse scope

Migration, Spark pipelines, Unity Catalog, ML, and GenAI on top. One team for the whole lakehouse, not a handoff between vendors.

ML and GenAI to production

Most models die in notebooks. We build the MLOps, feature pipelines, and serving layer that get them deployed, monitored, and actually used.

Governance from day one

Unity Catalog access controls, lineage, and audit built in early, so regulated industries like fintech and healthcare pass review without a retrofit.

Cost under control

We right-size clusters, tune jobs, and cut idle compute, so the platform scales without the bill scaling with it.

Build your data intelligence platform on Databricks.

Unify analytics and AI on one lakehouse, give every team the same governed data, and scale ML built for the modern enterprise.

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What we deliver

Our Databricks services

Migration to Databricks

Move off legacy warehouses, Hadoop, or scattered data lakes onto the lakehouse. We migrate in phases, reconcile against the source, and run parallel until you trust the new platform.

Data engineering & pipelines

Build and maintain Spark and Delta Live Tables pipelines that feed the lakehouse, orchestrated and tuned to hold up as volume grows.

Lakehouse architecture

Design the Delta Lake foundation, medallion layers, and table structure that let analytics and ML run on the same governed data.

ML & MLOps

Take models from notebook to production with MLflow, feature stores, and serving pipelines that stay monitored and reproducible.

GenAI on Databricks

Build RAG systems, agents, and LLM applications on Mosaic AI, grounded in your own governed data instead of generic models.

Unity Catalog & governance

Centralized access controls, lineage, and audit across every workspace, so the lakehouse stays compliant and consistent as teams grow.

Real-time & streaming

Structured Streaming architectures for fraud detection, telemetry, and operational data that has to land and react in seconds.

Cost optimization

Right-size clusters, tune Spark jobs, and cut idle compute to bring Databricks spend down without slowing anything that matters.

BI integration

Connect Databricks to Power BI, Tableau, and Looker with Databricks SQL and a clean semantic layer, so every team queries the same source.

Deep domain expertise

Databricks expertise across industries

Fintech

Real-time payments analytics, fraud detection, and governed lakehouse data for regulated financial workloads.

Healthcare

Patient and operational analytics on Databricks with HIPAA-aware governance and secure data sharing.

Retail & E-Commerce

Unified Shopify, marketplace, and ad data into one lakehouse for merchandising and growth.

Logistics

Spark pipelines that turn fleet, route, and warehouse data into real-time operational visibility.

SaaS

Product, billing, and usage analytics consolidated on the lakehouse so every team works from the same metrics.

Manufacturing

Sensor, supply-chain, and production data unified for forecasting and operational efficiency.

Food & Beverage

Manufacturing and distribution data engineered for traceability, demand, and yield insight.

Put a certified Databricks partner on your data.

Wherever you are — migration, pipelines, ML, or GenAI — our team can help. Start with a conversation.

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Common questions

Frequently asked questions

A Databricks partner is a firm certified to design, build, and run on the lakehouse. Brilworks brings certified engineers who have shipped Spark, Delta, and ML in production across fintech, healthcare, and manufacturing, not just teams who trained on the platform.
Most migrations run 8 to 16 weeks depending on data volume and how many pipelines and downstream systems depend on the old setup. We migrate in phases and run the old platform in parallel, so you move when you trust the new one, not before.
Yes. This is where most projects stall. We build the MLOps around your models with MLflow, feature stores, and serving pipelines, so they get deployed, monitored, and stay reproducible instead of dying in a notebook.
Yes. We build agents, RAG, and LLM applications on Mosaic AI, grounded in your own governed data through Unity Catalog. That keeps answers tied to your data instead of a generic model guessing.
We right-size clusters, tune Spark jobs, set auto-termination, and cut idle compute. Databricks bills on usage, so most savings come from jobs that were over-provisioned or running longer than they need to.
Databricks runs on AWS, Azure, and GCP, and we deliver on all three. We work in whichever cloud you already use, so there's no forced migration to a new provider.