Data Warehousing

  • Warehouse Design - Dimensional modeling (Kimball), medallion (bronze/silver/gold), or lakehouse patterns.
  • Platforms - Google BigQuery, SQL Server, PostgreSQL, Snowflake.
  • Modelling & documentation — proper facts, dimensions, SCDs, and clear lineage.

ETL / ELT Pipelines

  • Batch pipelines - Python + Airflow, SSIS, dbt.
  • Streaming - Pub/Sub, Kafka where near-real-time matters.
  • Ingestion from anywhere - REST APIs, files, databases, SaaS tools.
  • Change data capture - replicate transactional data into the warehouse without heavy queries on production.

Systems and APIs talking to each other

  • Custom Integrations - Get your CRM, warehouse, finance and marketing tools sharing data cleanly.
  • API design & build - REST or GraphQL, versioned, documented, authenticated.
  • iPaaS work - Zapier, Make, n8n, or writing custom middleware when the off-the-shelf option won't stretch.

Dashboards & automation

  • BI dashboards - Looker Studio, Power BI, Metabase.
  • Alerting & automation - Turn insights into actions your team can trust.