Giving-Tuesday / data-engineer-interview

Source Code for Data Engineer Technical Interview Exercise

data-engineer-interview

Giving Tuesday Data Engineer Technical Interview Exercise

The goal of this exercise is to aggregate some raw volunteering data from 3 different providers into a single dataset by implementing an ETL pipeline.

You have been given a Jupyter notebook notebooks/Volunteer Data Cleaning.ipynb which already implements a pipeline but you should find ways to improve upon that implementation by refactoring the code into Python modules.

Here are the requirements:

• The source data for your pipeline are the CSV files in data_lake/raw/2023/05
• The destination for your aggregated data should be data_lake/curated/2023/05/aggregated_volunteering_data.csv
• The following command must be able to run the pipeline:

poetry run python -m etl.volunteering.aggregate_data

• You must implement the entrypoint function in etl.volunteering.aggregate_data
• You must use the Task class in etl.common at least once
• You cannot make changes to the Task class in etl.common
• You should include at least one test for your pipeline in tests

Poetry and Useful Commands

This repo uses Poetry for dependency management.

Here are some commands you may need to know:

poetry install: Installs project dependencies (defined in pyproject.toml)

poetry add <package name>: Adds package to project dependencies and installs it into the project's virtual environment

poetry run python <path to your script> or poetry run python -m <module name>: Runs your script in the virtual environment

poetry run python -m pytest: Runs tests in the virtual environment

poetry shell and exit: Activates virtual environment in a new shell