Data Engineering Mastery Path¶

Mastery Path

BOOTCAMP

VINOD BHANUJA

A structured, module-wise training program on data engineering — from your first pandas script to production-grade, master-level data platforms — with runnable Python code in every module and a hands-on project at the end of each level.

Data engineering is the discipline behind every dashboard, ML model, and report a company relies on: moving data reliably from where it's produced to where it's needed, in a shape people can trust. This site teaches that discipline from first principles — plain Python and SQL first, frameworks (Airflow, Spark, dbt) once you understand what they're automating.

How the program is organized¶

Level	Focus	Modules
Level 1 · Entry	Python & SQL for data work, ETL fundamentals, data modeling, file formats, batch processing, orchestration concepts, data quality	9 topics + 1 project
Level 2 · Intermediate	Advanced SQL, API ingestion, warehousing, Airflow, partitioning, Parquet/Arrow, pipeline testing, streaming basics, dbt	9 topics + 1 project
Level 3 · Advanced	Spark, advanced Airflow, data lakes, streaming, governance, CI/CD, performance tuning, cloud warehouses, monitoring	9 topics + 1 project
Level 4 · Master	Enterprise architecture, real-time streaming at scale, data mesh, compliance, cost optimization, MLOps overlap, reliability engineering	9 topics + 1 capstone

What you need¶

Python 3.10+ and pip. Level 1 uses only the standard library and pandas — no cloud account, no API key, everything runs locally.
SQL is taught against SQLite, which ships with Python — no server to install.
Later levels introduce Airflow, Parquet/Arrow, dbt, and Spark; each lesson states exactly what to install before you start.

How to use this site¶

Work through each level in order — later modules assume earlier ones.
Every topic page has runnable code — copy it into a local .py file and run it. Every output block on this site was actually executed, not invented.
Each level ends with a project that combines everything learned in that level.
Use the search bar (top of the page) to jump straight to a topic.

Start here → Level 1 · Entry

Data engineering sits next to analytics, ML, and application development. Sister sites cover the neighboring ground: