Databricks Consulting & Data Engineering Services
Branchnode Technology builds and optimizes Databricks lakehouses: Delta Lake foundations, Spark pipelines that scale, Unity Catalog governance, and the MLflow workflows that take machine learning from notebook to production. We help teams stand Databricks up, migrate onto it from Hadoop or legacy Spark, and tune the clusters and jobs they already run. We are a US-based team working with clients nationwide and worldwide.
Tell us about your Databricks project and we will respond within 24 hours.
Databricks Lakehouse Implementation
We set up your Databricks workspace, Unity Catalog, and a Delta Lake foundation organized as a medallion architecture, bronze for raw, silver for cleaned, gold for analytics-ready. You get one platform that handles both heavy data engineering and analytics, modeled around your business rather than the shape of your source data.
Spark Pipelines & ETL
We build batch and streaming pipelines in PySpark and SQL, using Delta Live Tables and structured streaming where they fit. The pipelines are tested, idempotent, and observable, so they scale to large volumes and recover cleanly from failure instead of silently producing the wrong numbers.
Migration to Databricks
We migrate teams onto Databricks from on-prem Hadoop, legacy Spark, or aging ETL. We do it in phases, validating output and keeping existing jobs running until the new platform is proven, so the business keeps its reporting and you avoid a risky single cutover.
Machine Learning & MLflow
Databricks is where data engineering and machine learning meet, and we use that. We build feature pipelines, train and track models with MLflow, and deploy them to batch or real-time serving, so the model that worked in a notebook actually runs reliably against live data.
Governance with Unity Catalog
We configure Unity Catalog for centralized access control, data lineage, and auditing across your workspaces. Each team gets exactly the access it should, you can see where every table came from, and governance is documented and audit-ready rather than tribal knowledge.
Cost & Performance Optimization
Databricks compute adds up fast. We right-size and autoscale clusters, enable Photon where it pays off, tune slow jobs and shuffles, and schedule workloads so you get the throughput you need without paying for idle capacity. On an existing workspace this is often the quickest win.
What You Get
- Databricks workspace and Unity Catalog setup
- Delta Lake medallion architecture (bronze/silver/gold)
- PySpark and SQL pipelines (batch and streaming)
- Delta Live Tables where they fit
- MLflow model training, tracking, and deployment
- Cluster, Photon, and job cost optimization
- Governance, lineage, and access controls
- Documentation and team handoff
Technologies
Related
Data Engineering Services →
Our full data engineering practice: pipelines, warehouses, and integrations.
Snowflake Consulting →
SQL warehousing and BI when you do not need a full lakehouse.
AI Integration Services →
Put the models you train on Databricks to work in your products.
Analytics & Reporting →
Dashboards and BI on top of your lakehouse.
Databricks Consulting: FAQ
What Databricks services do you offer?
Should we use Databricks or Snowflake?
Can you migrate us from Hadoop or legacy Spark to Databricks?
Do you build machine learning pipelines on Databricks?
Do you set up Unity Catalog and governance?
How much does a Databricks project cost?
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