Service
Data Infrastructure
Data infrastructure should quietly carry the work placed on it. We build warehouses and pipelines that are proportionate, understandable and monitored properly.
What you get
- Data warehouse design, build and migration (including Redshift to Snowflake)
- Pipeline development and scheduled data workflows
- BI estate migrations — moving dashboards, datasets and users without breaking reporting
- Usage auditing — find out which datasets are actually used before you pay to move them
- Cloud cost, security and IAM hygiene
- Snowflake
- Redshift
- AWS
- DuckDB
- SQL
- Python
Move what the business actually uses
Warehouse migrations become expensive when everything is treated as equally important. We start with use: which datasets people rely on, how fresh they need to be and what can be left behind. Then we move what matters and compare every output with the original before anyone switches over.
Right-sized infrastructure
We pick the smallest stack that comfortably carries the work—a single-node warehouse where that is enough and a cloud platform where it is not. The business should not have to support an enterprise-shaped system for a problem that never needed one.
Reliability as a feature
Scheduled jobs, monitoring and useful alerts are part of the system, not a later tidy-up. A pipeline will fail eventually; the important thing is that the right person knows quickly and can see what happened.