Internal engineering · Data platform
One automated pipeline that collects data from our databases, spreadsheets and external websites, validates and loads it, refreshes every downstream report, and submits the final outputs — four times a day, with no manual steps.
Every run moves through the same four stages. A stage only starts when the previous one finishes cleanly; failures stop the run and raise an alert instead of submitting bad data.
Connectors pull raw data from each source on schedule — SQL queries against the databases, Excel workbooks from shared drives, scrapers and APIs for the websites.
Files and feeds are parsed, checked against expected schemas, deduplicated, and loaded into staging tables in the warehouse. Bad rows are quarantined, not dropped.
Curated models recalculate on the new data, and every downstream dashboard and report refreshes automatically — no one re-runs anything by hand.
Final outputs are exported and delivered: the daily filing goes to the submission portal, stakeholders get the digest, and a snapshot is archived for audit.
Three kinds of sources feed the pipeline. Everything lands in one warehouse, so reports and submissions always read from a single, validated copy of the data.