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# I Thought Data Engineering Was Just Writing Scripts. I Was Wrong.

**[Towards Data Science](https://daily.dev/sources/tds)** · 9 min read · 1 upvotes · 0 comments

## Summary

A data analyst documenting their transition to data engineering shares lessons from upgrading a basic ETL pipeline to be more production-ready. Three key problems emerged: duplicate data from re-runs (solved with idempotency using SQLite upserts), data loss between sessions (solved by persisting the database to Google Drive), and the need for automated scheduling (identified as the next frontier with tools like Airflow and Prefect). The post concludes that data engineering is fundamentally about building reliable systems, not just writing scripts.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://towardsdatascience.com/i-thought-data-engineering-was-just-writing-scripts-i-was-wrong>

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---

Tags: [#data-engineering](https://daily.dev/tags/data-engineering), [#etl](https://daily.dev/tags/etl), [#python](https://daily.dev/tags/python), [#sqlite](https://daily.dev/tags/sqlite)

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