Data Engineering Projects for Beginners You Must Know in 2025

Are you looking for Data Engineering Projects for Beginners? If yes, then this article is for you. In this article, you will find the Top 5 Data Engineering Projects for Beginners.

These projects will help you to learn and boost your data engineering skills. And also help you to make your portfolio stronger.

So, If you already gained Data Engineering fundamentals, I would suggest you pick a project from this list and start working on it.

Now without any further ado, let’s start finding the Data Engineering Projects for Beginners.

Data Engineering Projects for Beginners

1. Crawling for Inflation

This is a real example. Someone put this project on GitHub and showcase his work. The objective of this project is to find inflation rates from the first principles.

He used Common Crawl as a data source. Common Crawl is able to pull tons of data from various sources in terms of web history and pull different pricing information to try to detect inflation. And then calculate if inflation was slightly different than the reported one.

Following technologies are used in this project-> Spark, AWS Athena, and Dash/Plotly.

You can check the project here.

2. Extract, Transform, Load (ETL)

ETL involves extraction, transformation, and loading. In extraction, you have to extract the data from the original source. The transformation required data preparation such as cleaning the data and making the data ready for processing.

The last step is loading the data into a target database.

If you work on an ETL project, it will help you to showcase that you are familiar with the Data Engineering process.

You can build an ETL Pipeline with Batch Processing and with Stream Processing.

This YouTube tutorial will be helpful for you to understand more about ETL->ETL with Python

3. Hashtag Cashtag Project

The goal of this project is to show various components of both sentiment analysis and stock price and tweets. And then see if they can correlate.

Somebody uploaded this project on GitHub. He used Kafka, Spark, Cassandra, HDFS, etc. This project will give you a good idea of these tools. You need to understand all these components if you are working on a project for your resume.

You can check the project here.

4. Scraping Rental Prices Into Druid

This project used different tools such as Dagster, Spark, Jupyter Notebook, and the Data Visualization tool Druid. The project creator scrapes a bunch of real-state data to get some price information in different areas, especially in Sweden.

The goal of this project is to tackle common data engineering challenges.

The full documentation of this project is available, so it is easy for you to understand the whole process.

You can check this project details here.

5. Stream processing with Azure Databricks

The goal of this project is to create a Data Repository. Data Repository is a huge database infrastructure where datasets are collected, managed, and stored for data analysis, sharing, and reporting.

This GitHub project uses data from a taxi company known as Olber. They assume that there are two separate devices sending data. 

The duration, distance, and pickup and dropoff locations are sent by the taxi meter.

You can check the complete project details here.

Conclusion

So these are some best Data Engineering Projects for Beginners. I hope you have found the most suitable project in this article for you. For more project ideas, you can check Kaggle, Datacamp, Coursera, DataFlair, etc.

If you have any questions, feel free to ask me in the comment section. I am here to help you. And If you found this article helpful, share it with others to help them too.

All the Best for your Data Engineering Journey!

Happy Learning!

Thank YOU!

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Though of the Day…

‘ It’s what you learn after you know it all that counts.’

– John Wooden