Embedded Delivery Expertise
Databricks engineers embedded in your team
The gap between data ambition and a buildable plan
Delivery capacity
The backlog is prioritised. The roadmap is signed off. The internal team is stretched across existing commitments and can't give the next initiative what it needs.
Depth of expertise
Strong engineers, but the gap between working in Databricks and running complex production workloads on it is real. The initiative needs someone who has been here before.
Speed to production
The PoC worked. Stakeholders are waiting. Getting it to production requires production-grade engineering architecture, testing, ops readiness not another sprint on the prototype.
The right expertise for your specific challenge.
Platform Engineering
Design, build, and operate production Databricks Lakehouses. Covers data modelling, pipeline engineering, Unity Catalog, and the operational layer that keeps the platform reliable at scale.
Data Migration
Move workloads from legacy environments - Snowflake, Synapse, Redshift, on-premise warehouses - to Databricks.
MLOps & AI Deployment
Move ML models and AI agents out of experimentation and into production on Databricks. Covers MLflow tracing and evaluation, Agent Bricks, Vector Search, Model Serving with AI Gateway, and the monitoring that makes AI repeatable, not just demonstrable.
Pipeline Optimisation
Diagnose and fix underperforming pipelines, inefficient queries, and runaway compute costs. The focus is production impact, not theoretical improvement, work that changes what you see in the dashboard next week.
Architecture & Governance
Design the architecture for a platform being built or restructured, covering workspace and network layout, ingestion patterns, data flows, Unity Catalog structure, and access control. These are the decisions that are expensive to undo later, so we make them before anything is built.
Team Enablement
Capability building embedded into the delivery work, not separated from it. Our expert works within your team, pairing with your engineers, reviewing code together, and explaining the reasoning behind each decision, so skills build up as the work gets done.
A platform your team inherits, not one it depends on us to run.
Our Databricks experts are working as part of your team during the engagement and document all architectural decisions and changes.
Step-by-step guidance for your team to monitor, debug, and maintain what was built. Written by the engineer who built it, so the details that matter don't get lost.
Your team learns through pairing, design and code reviews, and documented decisions throughout the engagement. Understanding grows at the same pace as the platform.
The final step in knowledge transfer that runs throughout the engagement. Dedicated sessions with your technical team bring everything together: what was built, how to run it, what to watch, and what the next natural build phase looks like. Any remaining gaps in context are closed, so work carries on at your side with the full picture.
