Master the Data Engineering
Pipeline — End to End
From raw ingestion to production-grade Spark jobs — structured tutorials, a live PySpark compiler, and interview prep. All free.
In-depth articles from practitioners
Real-world insights on Data Engineering, PySpark, AI and more — written by engineers who build these systems daily.
PySpark Blogs
DataFrames, Spark SQL, Delta Lake, streaming and real-world ETL pipelines explained with code.
Data Engineering
Pipeline design, orchestration with Airflow, cloud platforms, dbt and modern data stacks.
SQL Blogs
SQL queries, joins, window functions, CTEs, performance tuning and analytics patterns.
Generative AI
LLMs, prompt engineering, RAG pipelines, LangChain and building AI-powered applications.
Machine Learning
Supervised learning, MLOps, feature engineering, model evaluation and Scikit-learn guides.
AI Agents
Building autonomous AI agents, multi-agent workflows, tool use and agentic frameworks.
From raw data to production pipelines
Every stage of a modern data pipeline, structured and explained with real PySpark code.
Transformation
Filter, join, aggregate and clean at scale using DataFrame and Spark SQL APIs.
Start →Storage & Lake
Write optimised Parquet, manage partitions and build lakehouse with Delta Lake.
Start →Orchestration
Schedule, monitor and retry complex pipelines with Airflow DAGs and best practices.
Start →Analytics & Serving
Serve clean data to BI tools, APIs and ML models from a well-modelled warehouse.
Start →Write & run PySpark
in your browser
No installation, no config. Write a Spark job, hit run, see the output — perfect for learning while you read.
- ✓ Full PySpark + Python support
- ✓ SQL executor with sample datasets
- ✓ Session-based execution engine
- ✓ 100% free — no login needed
Explore by Technology
Structured tutorials for every tool a modern data engineering team uses.
Where are you
right now?
Pick your level — we'll show you exactly where to start in the Data Engineering stack.
Choose the role you want to grow into
Follow a curated path mapped to how real data teams hire and work.
Data Engineer Path
Go from Python and SQL fundamentals to Spark, ETL pipelines, lakehouse patterns, and interview readiness.
Analytics Engineer Path
Learn SQL, data modeling, metrics thinking, and the workflows that power trusted reporting.
ML Engineer Path
Build a practical machine learning foundation with feature engineering, evaluation, and deployment thinking.
AI Engineer Path
Move from LLM basics to RAG, agents, evaluation, and production AI application design.
Skills teams are hiring for in 2025
Trusted by data professionals across India
"PySpark.in helped me go from zero Spark knowledge to cracking my data engineering interview in under 3 months. The structured tracks are exactly what was missing from other resources."
"The interview Q&A section is gold. Every question I was asked in my TCS ML round was covered here. The explanations go beyond definitions — they explain the "why"."
"Being able to run PySpark code directly in the browser without any setup was a game-changer. I could test concepts immediately while reading tutorials."
"I love how the content goes from Python basics all the way to GenAI without jumping between ten different sites. PySpark.in is my single learning hub now."
Start your Data Engineering journey today
Join 10,000+ learners building real pipeline skills in PySpark, Spark SQL, Airflow and more.