Databricks
consulting services
Get a Databricks roadmap tied to results
What our Databricks consulting services cover.
Grounded strategy and assessment
Every engagement starts with an audit of your environment: what's running, what's costing you in technical debt, and where the gaps sit against what you actually need. From there, we build a Databricks roadmap tied to ROI targets, so you know what to expect before a single cluster gets configured.
Databricks implementation and lakehouse architecture
Our Databricks implementation services start with workspace and cluster setup, followed by the Bronze, Silver, and Gold layers of a medallion architecture, CI/CD, and security locked down. What you launch with is what you can still run in two years, backed by full documentation and a trained team.
Clean Databricks modernization
Moving off Hadoop, a legacy data warehouse, or another cloud rarely goes as planned. Our team builds a phased migration roadmap and validates the data at every step. Within our Databricks migration services, downtime stays minimal, whether that's a full warehouse modernization or a Snowflake-to-Databricks move.
Reliable data engineering and pipelines
Pipelines run on Apache Spark and Delta Live Tables, with Auto Loader and Structured Streaming handling anything that arrives in real time. As part of our Databricks services, if your team is still maintaining Airflow or Azure Data Factory jobs nobody wants to touch, we migrate those too and keep everything documented.
Audit-ready Unity Catalog governance and security
An audit shouldn't be the moment you find out your access controls don't hold up. As a Databricks consulting partner, we implement Unity Catalog with role-based and attribute-based access control, column masking, and row-level security, mapped to GDPR, HIPAA, or SOC 2 requirements, with full data lineage built in.
Production-ready AI, ML, and MLOps
Models that live in a notebook don't help anyone. The Brights team builds the full loop: MLflow for tracking and the model registry, CI/CD for deployment, and drift detection to catch issues early. AutoML and a Feature Store keep retraining automatic instead of manual, so models stay useful well after launch.
Governed generative AI and AI agents
GenAI on Databricks moves fast, and most agents ship without guardrails. As your Databricks implementation partner, we build ours with Agent Bricks, the Databricks Agent Framework, and Mosaic AI, grounded in your own data through Vector Search and RAG. Evaluation and guardrails go in before anything reaches a user.
Transparent Databricks cost optimization
If your Databricks bill doesn't match what you provisioned, something in your Spark execution plan or cluster setup is off, often left over from a rushed Databricks modernization project. Our experts tune execution plans, fix partition skew, right-size clusters, and set up cost-tagged pools FinOps can track.
Get matched to the right service
When to bring in a Databricks consulting partner.
Migrating off Hadoop or a legacy warehouse
Migrations rarely fail on the technology. They fail on sequencing: what moves first, what breaks if it moves too soon, and who catches the data that doesn't reconcile along the way. Brights has run this sequencing before, on more than one legacy warehouse, and knows the right order.
Building your first lakehouse
Your first medallion architecture sets the pattern that every pipeline after it will follow. Get the Bronze, Silver, and Gold layers wrong at this stage, and you're refactoring for years. We've shipped 300+ projects, and know how to get the lakehouse foundation right the first time.
Rolling out governance
Unity Catalog touches every team that queries data, and rolling it out wrong means access requests piling up for months. Brights maps this against GDPR, HIPAA, and SOC 2 before touching a single permission and picks the right access model the first time.
Rescuing a runaway Databricks bill
When the Databricks invoice stops making sense, the fix is usually a specific misconfiguration: an oversized cluster, a bad partition strategy, autoscaling turned off somewhere nobody remembers. We find that root cause in days and fix it without disrupting anything still running.
Shipping GenAI on a deadline
Building enterprise agents on Mosaic AI or Agent Bricks takes specific experience that most in-house teams haven't had time to build yet. Brights gets you live in weeks. Hiring and training a team from scratch means a recruiting cycle first and a learning curve afterward.
Running things once your team is trained
Once your lakehouse is running and your engineers are trained on it, day-to-day operation belongs in-house. This is where you stop paying for work your team can now own, and Brights hands off cleanly, whether we ran one phase or the whole engagement.
How Databricks engagements with Brights work.
The tech stack we already work with.
Any cloud, no lock-in.
“We don't carry a single cloud partnership to protect. Our Databricks consulting services get deployed wherever your data already sits, on whichever cloud your team already runs. The deployment target gets chosen based on your setup.”
Databricks consulting vs. managed services.
What managed services cover
Once the build is done, your Databricks environment still needs attention. We monitor pipelines and infrastructure around the clock, catch performance drift before it turns into a support ticket, and keep cost optimization running as a continuous job rather than a one-time fix. Incident response and platform upgrades come standard, backed by an SLA you actually get to see.
When you need managed services
A lean team that can't staff round-the-clock Databricks operations still needs the platform to run reliably, and that's the gap managed services fills. Once your team has the headcount and training to run it themselves, it becomes optional. Brights builds the platform, then runs it through managed services, so you choose when one ends and the other starts.
Why companies choose Brights for Databricks services.
Brights holds Bronze partner status with Databricks, which means our engineers train on the platform directly and stay current as Databricks ships new features. You're not getting a team learning Unity Catalog or Mosaic AI on your project.
FAQ.
Brights runs a focused environment setup for Databricks implementation services in a few weeks. A full enterprise migration takes several months, and we scope the exact timeline after our discovery and environment audit, once we've seen your actual data volume and pipeline complexity.
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