Services / Platform
Data platform engineering
Nilaad designs and builds data platforms: the warehouse or lakehouse, the pipelines that fill it, the models that make it usable and the checks that keep it right. We work on Google Cloud and BigQuery, Snowflake, Databricks, and Microsoft Azure and Fabric, and we recommend a platform based on your workloads and your team.
When to call us
- You are setting up a first warehouse and want the structure right from the start.
- Pipelines break often and nobody trusts the numbers downstream.
- You are moving off a platform that no longer fits.
- Platform costs are climbing faster than usage.
What we do
- Platform selection and architecture.
- Ingestion and transformation pipelines, with dbt or the platform's own tools.
- Data models for analytics and for AI use.
- Data quality tests, monitoring and alerts.
- Access control, cost controls and documentation.
What you have at the end
A running platform in your own cloud account, with tests and documentation, handed over to your team.
Questions
Which data platform should we choose?
It depends on what you already run, the skills in your team and the workloads you expect. In our view BigQuery suits companies already on Google Cloud, Snowflake suits SQL-centered teams that want little infrastructure work, Databricks suits heavy data science and streaming, and Fabric suits companies standardized on Microsoft. We compare them against your case in the diagnostic.
Where does our data go?
It stays in your cloud accounts. We work inside your environment with access that you grant and can withdraw.