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.
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.
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.
Migration, Spark pipelines, Unity Catalog, ML, and GenAI on top. One team for the whole lakehouse, not a handoff between vendors.
Most models die in notebooks. We build the MLOps, feature pipelines, and serving layer that get them deployed, monitored, and actually used.
Unity Catalog access controls, lineage, and audit built in early, so regulated industries like fintech and healthcare pass review without a retrofit.
We right-size clusters, tune jobs, and cut idle compute, so the platform scales without the bill scaling with it.
Unify analytics and AI on one lakehouse, give every team the same governed data, and scale ML built for the modern enterprise.
Let's connectMove 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.
Build and maintain Spark and Delta Live Tables pipelines that feed the lakehouse, orchestrated and tuned to hold up as volume grows.
Design the Delta Lake foundation, medallion layers, and table structure that let analytics and ML run on the same governed data.
Take models from notebook to production with MLflow, feature stores, and serving pipelines that stay monitored and reproducible.
Build RAG systems, agents, and LLM applications on Mosaic AI, grounded in your own governed data instead of generic models.
Centralized access controls, lineage, and audit across every workspace, so the lakehouse stays compliant and consistent as teams grow.
Structured Streaming architectures for fraud detection, telemetry, and operational data that has to land and react in seconds.
Right-size clusters, tune Spark jobs, and cut idle compute to bring Databricks spend down without slowing anything that matters.
Connect Databricks to Power BI, Tableau, and Looker with Databricks SQL and a clean semantic layer, so every team queries the same source.
Real-time payments analytics, fraud detection, and governed lakehouse data for regulated financial workloads.
Patient and operational analytics on Databricks with HIPAA-aware governance and secure data sharing.
Unified Shopify, marketplace, and ad data into one lakehouse for merchandising and growth.
Spark pipelines that turn fleet, route, and warehouse data into real-time operational visibility.
Product, billing, and usage analytics consolidated on the lakehouse so every team works from the same metrics.
Sensor, supply-chain, and production data unified for forecasting and operational efficiency.
Manufacturing and distribution data engineered for traceability, demand, and yield insight.
Wherever you are — migration, pipelines, ML, or GenAI — our team can help. Start with a conversation.
Let's connect