Data pipelines & automation

What this looks like

Good data work is invisible. It just runs. Bad data work is the reason your Monday morning starts with "the dashboard is wrong again." We build the invisible kind.

We design and build data pipelines that extract, transform, and load your data reliably. Not fancy for the sake of it. Right-sized for your volume, your team, and your budget.

What we deliver

• ETL/ELT pipelines using Python, SQL, dbt, or Azure Data Factory
• Data orchestration with managed services or lightweight schedulers
• Data quality checks and alerting so failures are caught, not discovered
• Data warehouse or lakehouse design on Fabric, Databricks, or SQL Server
• Automated reporting pipelines feeding Power BI or Streamlit dashboards
• Pipeline documentation and runbooks for your ops team

How we work on this

We map your data sources and downstream consumers first. No point building a pipeline if nobody agrees on what "correct" means. Then we build iteratively: one source at a time, tested and monitored before moving to the next. You get working pipelines each week, not a big-bang go-live. Handover includes runbooks and a walkthrough with whoever will be on call.

Who this is for

Teams drowning in spreadsheets, manual exports, and "can you just pull that number?" requests. If your data workflow depends on one person who knows the magic sequence, we can fix that.