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24 alternativesData Engineering Practice Problems
Data Engineering Practice Problems provides exercises for practicing data engineering skills.
About Data Engineering Practice Problems
Data Engineering Practice Problems is a GitHub repository of exercises for practicing data engineering skills. It covers Python data processing of CSV, flat-file, Parquet and JSON files, SQL table design, Python and Postgres data ingestion, PySpark, and cleansing of dirty data. The exercises are arranged in beginner, intermediate and advanced groups, from downloading files over HTTP to data quality checks with Great Expectations.
Each exercise is run from its own folder using a Docker build command listed in that exercise's README. The tools needed for each exercise are packaged in its Dockerfile, and running the exercises requires Docker and docker-compose.
Key features
- Python exercises for processing CSV, flat-file, Parquet and JSON files
- Downloading and unzipping files from an HTTP source with Python
- Web scraping and Pandas exercise with cumulative calculations
- Boto3 exercise for downloading open source files from AWS S3
- Converting JSON to CSV from a ragged directory structure
- Progressive exercises on PySpark, DuckDB, Polars and Great Expectations
Best for: Learners who want hands-on practice with Python, SQL and data engineering tools and are comfortable working with Docker.
Good for
- Exercises progress from beginner to advanced topics.
- Tools for each exercise are packaged in its Dockerfile, so they do not need to be installed separately.
- Covers a range of tools, including Postgres, PySpark, DuckDB, Polars and Great Expectations.
Watch out for
- Running the exercises requires Docker and docker-compose.
- Each exercise must be run from its own folder with a separate build command listed in its README.
Data Engineering Practice Problems at a glance
- Category
- Education & Learning › Learn to Code
- Type
- Open-source project
- Pricing
- Not confirmed. Check the site
- Open source
- Not stated
- Language
- English
- Last checked
- Oct 6, 2026 · Online when checked
- Listed
- Oct 5, 2026
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Data Engineering Practice Problems FAQ
What do I need to run the exercises?
Docker and docker-compose. The tools and technologies for each exercise are packaged into its Dockerfile.
How do I start an exercise?
Change into the exercise folder, such as Exercises/Exercise-1, and follow the docker build instructions in that exercise's README.
Which tools are covered?
The exercises cover Python, SQL with Postgres, PySpark, DuckDB, Polars, Great Expectations and boto3 for AWS S3.
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