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Data Integration & Engineering

Pipelines, lakes and warehouses that turn scattered data into reports people trust.

Two people planning a project with sticky notes on a glass wall

The problem

When every department exports its own spreadsheets, nobody agrees on the numbers. A well-designed data platform ends the argument.

What we build

  • ETL and ELT pipelines with Azure Data Factory
  • Data lakes with medallion (bronze/silver/gold) architecture
  • Databricks and Spark processing
  • Warehouses on Snowflake, Azure SQL or PostgreSQL
  • Data quality checks, lineage and scheduling

Who it is for

  • Companies with data in many systems and no single view
  • Organizations preparing data for AI and analytics
  • Teams tired of manual report building

Typical examples

Large-scale public-health data lake

Ingested large data sets into Azure Data Lake using a medallion architecture with Data Factory, Databricks and Python.

Ready to talk about data integration & engineering?

Tell us what you need. You get a reply from an engineer within one business day, with clarifying questions or a proposed time for a short call. No sales pitch.