Data pipelines
Move records, not mountains
Sync rows between stores, fan out events from queues, and keep warehouses fresh, with retries and logging built in.
The problem
The space between 'a cron script' and 'a data platform' is where most teams live: too small for Airflow, too important to lose silently.
After the flow
Pipelines that retry themselves, log every payload, and page you only when something actually breaks.
Three flows teams actually run
Kafka fan-out
Events from a topic are filtered, transformed, and delivered to three downstream systems with per-step retries.
Nightly reconciliation
Stripe payouts are compared against the ledger and discrepancies become a morning report, not a quarter-end surprise.
Sheet to source of truth
Edits in the ops team's Google Sheet validate and upsert into Postgres, so the sheet stays useful and the database stays right.
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