Everything you need to become
a job-ready Data Engineer
Master the 9-stage engineering curriculum (61 videos • 167.6 hours), execute 500 industrial coding problems with in-browser DuckDB WASM, and deploy production portfolio capstones — 100% unlocked with zero paywalls.
100% Free Open Access • Zero Paywalls • Industry-Standard Masterclasses
Raw event streams & batch extracts via Kafka, Azure Data Factory, & Cloud Storage.
Cleaned, deduplicated, & partitioned datasets using Apache Spark & dbt transformations.
Star schemas, aggregated business marts, & sub-second DuckDB WASM queries.
Trusted by 25,000+ Aspiring & Working Data Engineers From Top Companies
Where are you starting from, and what is your goal?
Tell us your current background. DataForge will calculate your career transition path and match the exact videos, 20-30 min modules, and projects suited for you.
Recommended Start: 20-30 min Python & SQL Foundation → Data Engineer / Lakehouse Architect Track
Based on your background, start with our 100% free bite-sized SQL and Python modules, then proceed to the distributed Spark and Lakehouse DAGs.
The DataForge Master
Engineering DAG 150
Stop guessing what to learn next. A structured dependency DAG tree designed for interview readiness and production-grade mastery — all nodes 100% unlocked.
Python for Data Engineers
Generators, memory profilers, typing, decorators, and OOP data structures.
Advanced SQL & Query Tuning
Window functions, recursive CTEs, EXPLAIN plans, indexing, and partitions.
Dimensional Modeling & Lakehouse Design
Kimball star schemas, SCD Type 2/4, conformed dimensions, factless facts.
Distributed Compute (Apache Spark)
Spark Catalyst optimizer, shuffle partitioning, Broadcast joins, PySpark memory.
Cloud Warehouses (Snowflake & BigQuery)
Micro-partitions, clustering keys, BigQuery slot reservations, zero-copy cloning.
Orchestration & Transforms (Airflow & dbt)
DAG scheduling, sensors, dynamic mapping, dbt models, incremental strategies.
Data Engineering System Design
Lambda vs Kappa, high-throughput ingestion, SLA budgeting, disaster recovery.
Pick the role. Follow the path.
Follow a complete career track, or focus on one skill at a time. Every path starts with the foundations and builds toward job-ready skills.
Data Engineer
Zero to job-ready data engineer — fundamentals, Python and SQL, modeling and warehousing, then Spark, orchestration, streaming, and the cloud, finishing with system design.
Analytics Engineer
Model and transform data for analytics — start with Python and SQL, then move through dimensional modeling, warehousing on Snowflake, and dbt for production transformations.
Streaming Systems Engineer
Build event-driven distributed systems using Apache Kafka, Spark Structured Streaming, Flink, and cloud messaging for sub-second data processing.
Master the tools companies actually use
Learn the high-demand data engineering stack — from cloud platforms to orchestration tools.
End-to-End Data Engineering Project | Uber Data Analytics | GCP, Mage AI, BigQuery & Looker
A complete real-world data engineering walkthrough modeling millions of Uber trips. Learn dimensional modeling (Fact & Dimension tables), modern orchestration with Mage AI, Google Cloud Storage, BigQuery data warehousing, and Looker Studio dashboarding.
Zomato AI Data Analytics | End-To-End AI Data Engineering Project
Build a next-generation AI-powered food delivery data pipeline. Ingest restaurant transaction feeds, perform geospatial customer analytics, clean data with Python, and leverage Generative AI for automated menu categorization and sentiment scoring.
Twitter Data Pipeline using Airflow for Beginners | Data Engineering Project
Build a production-grade automated ETL pipeline orchestrating Twitter streaming data with Apache Airflow. Provision Amazon EC2, write custom Airflow DAGs with Python operators, extract tweets, and store refined Parquet datasets into Amazon S3.
AWS Masterclass for Data Engineers with End-to-End Project
Master the AWS Data Stack. Connect Amazon S3 data lakes with AWS Lambda serverless compute, crawl schema evolution with AWS Glue Data Catalog, run distributed Spark transformations, and execute serverless SQL queries with Amazon Athena.
Intro to Data Build Tool (dbt) | Create Your First Production Project with Snowflake
Master dbt Core from scratch with Snowflake. Setup profiles.yml, build staging views, modularize SQL transformations with ref(), configure schema tests (unique, not null), and generate live lineage documentation.
Apache Kafka Crash Course | Real-Time Event Streaming from Scratch
A definitive guide to distributed event streaming with Apache Kafka. Deep dive into topics, partitions, broker clusters, producer ack semantics, consumer groups, offset commits, and Kafka vs traditional message brokers.
From “Where do I start?” to interview-ready.
Choose your goal, follow the right learning order, validate each skill, and prove you can apply it.
Learn in the right order
A guided path from foundations to advanced skills.
Validate every skill
Assessments and quizzes reveal what you truly know.
Prove you can apply it
Turn knowledge into practical, verifiable skill with 23 projects.
Get interview-ready
Prepare with 850+ coding problems and system design.
Prerequisite sequencing prevents tutorial hell
Your path follows strict prerequisite order, so every lesson builds directly on the concepts proven before it.
Thirteen tools, one outcome — the version of you that walks out with the offer.
Everything integrated in one place with zero subscription paywalls.
Coding Problems
500 industrial SQL, Python, PySpark, Data Modeling & System Design problems (5 topics × 5 modes) with zero-setup in-browser DuckDB WASM execution.
Curated Video Tutorials
Full-length, high-definition masterclasses embedded directly with interactive timestamp chapters, code snippets, and key takeaways.
Real-World Projects
23 production-grade data pipelines (Uber GCP, Spotify AWS, YouTube ETL, Kafka Real-Time) with architecture diagrams and GitHub repositories.
Data Model Playground
Design and validate Star Schemas, Snowflake Schemas, and SCD Type 2 dimension tables directly in your browser.
Architecture Playground
Solve real-world distributed systems, capacity planning, and streaming architectures before your system design interviews.
Structured Learning Paths
Zero to job-ready roadmaps curated by senior engineers, preventing tutorial hell with structured prerequisite sequencing.
Cloud Labs
Hands-on guided walkthroughs executing data workloads across AWS, GCP, Azure, Snowflake, and Databricks.
AI Resume Evaluator
Real-time ATS diagnostics, keyword coverage matching against target job descriptions, and Google XYZ bullet improvements.
The Vault (Book Library)
Read the complete industry textbooks online: Kimball Data Warehouse Toolkit, Designing Data-Intensive Applications, Databricks Lakehouse, and 13 other canonical works.
Article Podcasts & Guides
300+ concise deep dives explaining Airflow internals, PySpark memory tuning, Kafka consumer groups, and data contracts.
Community Solutions
Explore optimal query solutions and benchmark executions contributed by engineers from Google, Amazon, and Stripe.
Karma & Leaderboard
Earn reputation points, unlock verified competency badges, and track your ranking across the engineering cohort.
Progress & Streaks
One sign-in, one progress record. Track consecutive daily commits and never lose your momentum.
Loved by data engineers worldwide
Real stories from 25,000+ engineers using DataVeda to land offers and level up their stack.
"DataVeda has been a great learning experience for me transitioning into Data Engineering. The structured learning path, practical projects, and clear explanations helped me understand concepts beyond just theory. The hands-on Spotify and Uber projects gave me confidence in real-world pipelines."
"The data lab in DataVeda platform is very useful for practicing coding problems. The in-browser execution is very helpful to understand how to simplify the code written based on time complexity and coding standards."
"When I started learning Data Engineering, I thought it was mainly about syntax and tools. DataVeda completely changed that understanding with its fundamentals-first approach and why-before-how explanations."
One plan. Everything you need to get hired.
No credit card required. No $279 annual lock-in. Everything unlocked and open.
DataVeda Master Curriculum
Curated with industry-standard top YouTube tutorials & real cloud labs.
Making data easier for everyone
"When we started building DataVeda, our vision was simple: Make data engineering accessible, practical, and career-defining. Data engineering isn't just about pipelines and tools; it's about solving real problems, building systems that scale, and enabling companies to make smarter decisions. Let's build the future of data, together."