Data platform engineering
A data platform should be run like software, not like a shared drive.
We build Databricks, Snowflake and Fabric platforms with infrastructure as code, tested pipelines and clear ownership — then hand them to your team.
The problem
What we usually find
Every workspace was configured by hand
Clusters, permissions and networking were clicked together. Nobody can rebuild the environment, and audits find drift every quarter.
Pipelines break silently
Jobs fail at 2 a.m. and the first alert is a business user asking why the dashboard is empty.
One person knows how it works
Knowledge sits with a contractor or a single senior engineer. When they leave, change slows to a crawl.
Our approach
Four steps, each with a deliverable
- 01
Reference architecture
We agree the target design: workspaces, environments, networking, identity, storage layers and naming — written down and reviewed by your security team.
- 02
Infrastructure as code
Everything is defined in Terraform and deployed through pipelines. Dev, test and prod are identical by construction.
- 03
Pipelines with tests
Ingestion and transformation code ships through CI/CD with unit tests, data tests and code review.
- 04
Operate and hand over
Monitoring, alerting and runbooks go live with the platform. Your engineers pair with ours until they run it alone.
Reference architecture
Deliverables
What you receive
- Reference architecture document approved by your security team
- Terraform modules for workspaces, networking, identity and storage
- CI/CD pipelines for data code with automated tests
- Monitoring dashboards, alert routing and runbooks
- Pairing and handover plan for your platform team
Typical timeline
How the work runs
Design2–3 weeks
Reference architecture, security review and backlog.
Foundation4–6 weeks
Environments, identity, networking and CI/CD live.
First domains6–10 weeks
Priority pipelines rebuilt on the new foundation.
Handover2–4 weeks
Your team operates with ours on call as backup.
Frequently asked questions
Do you work in our cloud accounts or yours?
Always yours. We build in your AWS, Azure or Google Cloud accounts, under your identity provider, so there is nothing to migrate when we leave.
Databricks, Snowflake or Fabric — which should we choose?
It depends on your workloads, skills and existing contracts. We have no reseller margin on any of them, and the Data Platform Assessment ends with a written recommendation and cost comparison.
Do you use dbt?
Where it fits. We use dbt, Delta Live Tables, Snowpark or Fabric Data Factory depending on the platform and what your team can maintain.
How big is a typical team?
Two to five senior engineers plus an architect. We do not staff junior consultants on client work.
What happens after go-live?
Your team runs the platform with our runbooks. If you prefer us to operate it, see our managed data platform service.
Have 30 minutes? Get a senior architect’s view of your data platform.
No sales deck. You talk to the engineer who would lead the work.
Book an architecture review