Expertise

A focused stack, engineered deeply.

We deliberately stay close to the technologies and patterns where we can deliver with confidence.

Core technologies

dbtSQLAzure Data Factory DatabricksPySparkDelta Lake ADLSREST APIsSFTPGit

Engineering patterns

  • Incremental ingestion & watermarking
  • Metadata-driven frameworks
  • Medallion / lakehouse architectures
  • Data quality & reconciliation
  • Production monitoring & alerting
  • Performance optimization

Reference solution patterns

These are representative solution patterns, not claims of completed UPOLE client engagements. They show the types of systems we are prepared to design and deliver.

Reference Architecture

Metadata-driven Azure ingestion

Configuration-led ingestion across multiple sources with reusable ADF orchestration, standardized logging and incremental-load controls.

ADF · SQL · ADLS · Databricks
Reference Architecture

dbt analytics engineering layer

Structured staging, intermediate and mart layers with tests, documentation and maintainable SQL transformation patterns.

dbt · SQL · Git
Reference Architecture

Production DataOps monitoring

Operational controls for pipeline failures, missing files, freshness, row-count anomalies and downstream-impact visibility.

ADF · Databricks · SQL · Alerts