Data & Cloud
Service 05 / 06
A foundation that scales quietly
We build the unglamorous layer that makes everything else reliable: schemas, pipelines, environments, deployment and cost visibility.
- Good fit if
- Reports disagree with each other.
- Typical stack
- Google CloudBigQueryCloud RunPostgresdbtTerraformGitHub Actions
Human approval is designed into any action that sends, submits or changes production data.
What changes
The outcome we are aiming for.
This is not a feature list. It is the operational change we want to see after the work is live.
One version of the truth
Releases that do not require heroics
Predictable cloud spend
Recoverable systems and clear ownership
What you get
A build with the edges included.
The demo is the easy part. These are the pieces that make it usable after the first week.
Data model and warehouse design
Batch and event pipelines
Infrastructure as code
CI/CD and environment strategy
Monitoring, backups and alerts
Cost and access reviews
How it runs
Three loops, not a waterfall.
We keep the feedback loop short so the expensive decisions happen after we have evidence.
Map the real workflow
We watch the current process, including the workarounds. The map includes the tools, the decisions and the exceptions.
Build the smallest useful slice
A working version goes in front of real users early. We measure whether it removes the friction before expanding scope.
Harden and hand over
Retries, approvals, alerts, documentation and training. You leave with a system your team can operate without us.
Keep exploring
Related capabilities.
Data & Cloud · 2–8 weeks
Let’s find the first useful slice.
Tell us where data & cloud is slowing the team down. We will come back with a concrete first step, not a generic pitch.