What this solves
Problems that get worse as you grow.
Queries that take hours.
Your reports are slow because your data infrastructure was not designed for the volume you now have. Dashboards time out. Analysis takes overnight.
Storage costs growing faster than revenue.
Data is piling up without a clear architecture. You are storing everything and querying nothing efficiently. Cloud costs are climbing.
Pipelines that break silently.
Data arrives late or incomplete and no one notices until a business decision gets made on wrong numbers. There is no monitoring in place.
What we build
Scalable infrastructure. Built to last.
Data warehouse architecture
BigQuery or Snowflake implementations designed for your query patterns, team structure, and cost constraints. Schema design, partitioning, and access control.
ETL/ELT pipelines
Extract, transform, and load pipelines that move data from source systems to your warehouse reliably. Built with dbt, Airflow, or n8n depending on your stack.
Real-time data processing
Streaming data infrastructure for use cases that cannot wait for a nightly batch — event processing, fraud detection, live dashboards.
Data lake implementation
Cost-effective storage for raw data at scale, with the query capability and governance layer to make it usable and not just a data swamp.
How it works
Assess, architect, implement.
Infrastructure assessment
We review your current data architecture, identify bottlenecks, and model the infrastructure that fits your scale and cost requirements.
Architecture & build
We implement the warehouse, pipelines, and monitoring layer. All infrastructure is documented with runbooks so your team can maintain it.
Performance tuning
We optimise for query performance and cost after go-live. Data infrastructure needs iteration — we stay involved through the stabilisation period.