> For the complete documentation index, see [llms.txt](https://data-engineering-zoomcamp-2025-t.gitbook.io/tinker0425/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://data-engineering-zoomcamp-2025-t.gitbook.io/tinker0425/module-2/2.2-etl-pipelines-in-kestra-detailed-walkthrough.md).

# 2.2 - ETL Pipelines in Kestra: Detailed Walkthrough

This week, we're gonna build ETL pipelines for Yellow and Green Taxi data from NYC’s Taxi and Limousine Commission (TLC). You will:

1. Extract data from [CSV files](https://github.com/DataTalksClub/nyc-tlc-data/releases).
2. Load it into Postgres or Google Cloud (GCS + BigQuery).
3. Explore scheduling and backfilling workflows.

This introductory flow is added just to demonstrate a simple data pipeline which extracts data via HTTP REST API, transforms that data in Python and then queries it using DuckDB. For this stage, a new separate Postgres database is created for the exercises.


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