I like building things, breaking them, and then understanding why they work the way they do.

Professionally, I work as a Data Engineer, mostly around data pipelines, Spark, Databricks, and cloud data platforms. But this GitHub is where I explore ideas, learn new concepts, and experiment with systems beyond day‑to‑day work.

My journey started with DSA, ML, SQL queries, and simple data transformations. Over time, curiosity pulled me deeper into how large‑scale data systems move, transform, store, and secure data behind the scenes. What began as basic data analysis evolved into designing and understanding data platforms that are reliable, performant, and scalable.

I've been exploring a mix of:

• 📊 Data Engineering & Analytics – ETL pipelines, data modeling, reporting, and hands‑on experiments.
• ⚡ Apache Spark & Databricks – batch/streaming jobs, execution plans, shuffles, partitioning, and performance tuning.
• 💾 Delta Lake & Lakehouse – transactions, merge operations, schema evolution, and lakehouse patterns.
• 🗄️ SQL & Database Systems – query design, indexing, optimization, and integrations with different databases.
• 🐍☕ Python & Java – scripts, utilities, backend concepts, and small services.
• 🧩 Data Structures & Algorithms – problem solving and writing efficient code for fun and learning.
• 🔄 Distributed Systems & System Design – thinking about scalability, reliability, and trade‑offs in real systems.
• 🔐 Security, Auth & Access Control – data governance, permissions, JWT auth, and secure data access.
• ☁️ Cloud & Platforms – cloud storage, lakehouse architecture, and modern data platform design.

What excites me most is going beyond “how to use a tool” and understanding the engineering behind it.