I’m thrilled to kick off a new project that’s been brewing in my mind for a while. Meet Lakeground — a fusion of a Data Lake and a playground, where the goal is to experiment, learn, and build a fully open-source, end-to-end Data Engineering stack. This project is all about exploring creative ways to solve data challenges using free tools, while keeping everything modular and fun to work with.
The idea behind Lakeground is to build something that feels like a sandbox for Data Engineering enthusiasts. Imagine a system where you can piece together components, break them apart, and experiment freely, all while building something functional. Each part of the stack will be its own standalone tool, designed to work independently but also integrate seamlessly with the others to form a complete pipeline.
This design approach comes with an exciting challenge: finding the right balance between modularity and interoperability. The components need to stand on their own, yet come together as a cohesive system when needed. It’s a puzzle I’m excited to solve, and I’m sure there will be plenty of lessons (and surprises) along the way.
I’m also eager to dive into the incredible ecosystem of open-source tools available today. Lakeground will be built with a focus on Python, and the stack will cover the full data lifecycle: ingestion, schema management, metadata tracking, transformation, data delivery, and visualization.
Why Lakeground?
Because Data Engineering should be more than just building pipelines for work — it should be a craft you can enjoy. While the professional side of Data Engineering often focuses on scalability, robustness, and solving business problems, there’s immense value in stepping back and just experimenting for the sake of learning.
Lakeground is my space to do exactly that. It’s a project where I can test out ideas, break things, and discover what works (and what doesn’t) in a low-pressure environment. And by sharing my journey, I hope to inspire others to dive into the world of open-source data tools and maybe even contribute ideas or improvements to the project.
What’s Next?
This is just the beginning. Over the coming weeks (and maybe months), I’ll be sharing updates on how Lakeground is shaping up. You can expect detailed write-ups on design decisions, hands-on exploration of open-source tools, and maybe even a few missteps along the way.
I’ll be setting up a central repository on GitHub with a monorepo-inspired structure, but each component of Lakeground will live as a separate directory (a submodule—meaning each directory is its own repository). These components will function independently while still being part of a cohesive stack. This modular approach makes it easier to experiment with specific tools or workflows without needing to set up the entire pipeline every time.
monorepo
A monorepo (short for monolithic repository) is a single Git repository that houses the code for multiple projects or components. Instead of separating each part of a system into its own repo, everything lives together, making it easier to share code, manage dependencies, and ensure consistency.
submodule
A Git submodule is a repository embedded within another repository. It allows you to manage multiple, independent projects while keeping them connected.
If this project sparks your curiosity, I’d be happy if you followed along with the journey. Whether you’re here for the code, the tools, or just the learning process, there’s plenty to look forward to. And if you have any suggestions, ideas, or tools you think I should explore, don’t hesitate to reach out!