Data Engineering & Governance
Pipelines that hold under load.
Untrusted data is the reason most dashboards get ignored. We fix it upstream: ingestion and orchestration across Microsoft Fabric Lakehouse, Snowflake or Databricks on Azure, with dbt and Data Factory transforms, reconciliation tests, lineage and access control built in from the first commit.
- Microsoft Fabric
- Azure
- dbt
- Snowflake / Databricks
- Lineage
- Data contracts
What we deliver
- Medallion-architecture lakehouse builds
- Orchestrated, observable, alerting pipelines
- Data contracts, testing and lineage documentation
- Access, retention and governance frameworks
Enterprise FAQ
- How long until our pipelines are reliable?
- A governed ingestion pipeline for your core source systems is typically running in production within 6–8 weeks, with reconciliation tests, alerting, and lineage from the first release.
- How do you approach data security and compliance?
- We implement least-privilege access, column and row-level controls, encryption at rest and in transit, and retention policies aligned to your regulatory requirements. Everything is documented for audit.
- What deliverables make this maintainable?
- Infrastructure-as-code, data contracts, automated tests, lineage diagrams, a data dictionary, and runbooks. Your platform team can operate, extend, and onboard new sources without us.
- Can you work alongside our existing data team?
- Absolutely. We embed with your engineers, follow your Git and deployment practices, and leave capability behind through pair programming and structured handover sessions.