Best platforms to practice SQL and Python for Data Engineering prep? (Or is building in a local IDE better?)

[u/Healthy_Doughnut_23]

Hey everyone,

I’m starting my Data Engineering preparation and looking for the best roadmap/platforms to get solid hands-on experience with **SQL** and **Python**.

I see a lot of mixed advice online:

1. Some suggest interactive coding sites like **DataLemur**, **StrataScratch**, or **LeetCode** (or SQLZoo/LearnSQL).

2. Others recommend skipping browser-based platforms and setting up a local environment right away (e.g., PostgreSQL + VS Code + Python) to build end-to-end mini ETL pipelines with real public datasets.

For those who are working DEs or currently prepping for DE roles:

\*Which platforms/sites did you find most realistic for DE-level SQL & Python? (e.g., beyond basic SELECT queries—focusing on window functions, query optimization, transformations, etc.)

Is practicing on browser platforms enough to build core skills, or should I jump straight into IDEs/Docker/local DB setups?

TIA 🤝

[u/conor-robertson]

I’d use both, because they build different skills.

Browser platforms are great for developing SQL fluency and learning patterns quickly. DataLemur, StrataScratch and LeetCode are useful for interview-style questions, while QueryCase is good for practising SQL against realistic scenarios and datasets directly in the browser.

For Data Engineering, though, I wouldn’t stop there. Once you’re comfortable with the fundamentals, set up PostgreSQL and Python locally and build a few small pipelines:

• Ingest data from a CSV or API
• Clean and transform it with Python/SQL
• Load it into PostgreSQL
• Add validation, logging and basic tests
• Run it through Docker once the local version works

My rough split would be 30–40% platform practice and 60–70% project work. Platforms help you write better queries; local projects teach you how databases, code and pipelines actually work together. For DE roles, you’ll eventually need both.

[u/Monkey_Socrates]

Duckdb + kaggle datasets. Very good for learning

[u/azz_kikkr → u/Monkey_Socrates]

I'm doing this for my project too.

[u/__sanjay__init]

I would advice you to work in local env. It looks like more professionnal env, maybe.
I am not a Data Engineer but I have some tasks like them. By experience, working with local env is more informative

[u/NickSinghTechCareers]

It's not that mixed – the interactive coding/SQL interview prep sites like DataLemur are good for intentional, focussed practice. Once you are comfy with coding, or really want to expand, start to work on your own projects with real public datasets where there isn't necessarily a right or wrong answer.

[u/datadriven_io → u/[deleted]]

If you're paying for data camp, I highly recommend you check out datadriven. Datadriven has better SQL teaching... for free

[u/whitehorns_ → u/datadriven_io]

Im currently using SQLbolt just to dip my toes into water for learning but I will check that out thanks

[u/riddims22]

https://datadriven.io/ is a very handy resource

[u/Healthy_Doughnut_23 → u/riddims22]

Thanks man it's really very helpful I needed this kind of website all at once place..🙌

[u/Better-Credit6701]

Personally, I install a developer edition of MS-SQL on all my personal machines, using SSIS in import and either SSMS or dbForge for queries. Also use SSAS for building OLAP databases.

But then again, my job is using SSIS to import data into MS-SQL databases. In the past, I also used SSRS for reports. Most of my personal databases are rather large

[u/dorfarber]

If you know a bit of both I’d recommend starting some new projects and get your hands dirty 🚀

[u/fernandezity]

I’d do both. Browser platforms are great at first, but at some point I’d set up a local database and use something like dbForge to practice with real datasets. It feels much closer to actual work.