Data
We turn raw data into strategic assets. Cloudsa's data engineering practice designs and operates pipelines, warehouses, and analytics platforms that give your organisation a reliable, governed view of its operations.
Capabilities
Batch and streaming pipeline design with Apache Airflow, Azure Data Factory, dbt, and Spark for reliable, observable data movement.
Snowflake, Azure Synapse, and Databricks implementations with optimised schemas, partitioning, and query performance.
Medallion architecture (bronze/silver/gold) on Databricks with Unity Catalog governance, Delta Lake, and AutoML.
Event-driven architectures with Apache Kafka, Azure Event Hubs, and stream processing for sub-second analytics.
Power BI, Looker, and Tableau deployments with semantic layers, row-level security, and automated report distribution.
Data lineage, quality frameworks, PII classification, and Microsoft Purview or Apache Atlas governance catalogues.
Years of delivery
Projects shipped
Platform uptime
Why Cloudsa
A decade of enterprise delivery, applied to your data challenge.
We have built data platforms for healthcare and financial services clients where data integrity, lineage, and access control are non-negotiable.
We use medallion architecture and Delta Lake patterns to deliver analytics platforms that are reliable, testable, and cheap to operate.
Whether you need batch aggregations or millisecond streaming, we design architectures that handle both without duplication of logic.
Our data engineering practice connects directly to our AI/ML team — the same data platform that powers your dashboards can power your models.
Let's discuss your requirements and map out a practical path to delivery.
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