Data Engineering Roadmap
From core fundamentals to advanced techniques — six stages, in order, each one building on the last, laid out to take you to a job-ready skill set.
TABLE roadmap (6 stages, ordered)
Foundations
Python, SQL, and the core concepts every data engineer needs before touching a pipeline tool.
BeginnerStorage
Design data lakes and warehouses that scale — built to be fast to query, not just cheap to store.
BeginnerTransformation
Turn messy, raw data into structured, reliable models with dbt.
IntermediateOrchestration
Automate and schedule pipelines with Airflow — the operational thinking that makes them production-ready.
IntermediateStreaming
Build real-time pipelines with Kafka to process data in motion, not just in nightly batches.
AdvancedGovernance
Lead data strategy and quality standards — the skills that turn a senior engineer into a tech lead.
AdvancedExplore each path
Every path includes guided lessons, hands-on labs, and a project you can add to your portfolio.
Foundations Path
Python, SQL, and the core concepts every data engineer needs before touching a pipeline tool.
Start pathStorage Path
Design data lakes and warehouses that scale — built to be fast to query, not just cheap to store.
Start pathTransformation Path
Turn messy, raw data into structured, reliable models with dbt.
Start pathOrchestration Path
Automate and schedule pipelines with Airflow — the operational thinking that makes them production-ready.
Start pathStreaming Path
Build real-time pipelines with Kafka to process data in motion, not just in nightly batches.
Start pathGovernance Path
Lead data strategy and quality standards — the skills that turn a senior engineer into a tech lead.
Start pathBrowse all courses
Every course belongs to a path, but you can start any of them on their own — filter by stage below.
Basic Python for Data Engineers
Learn the syntax, scripting patterns, and automation habits that make later pipeline work easier.
SQL for Data Engineers
Write the queries, joins, and window functions that show up in every data engineering job.
Data Lakes & Warehouses Fundamentals
Design storage layers that scale — and understand when to reach for a lake versus a warehouse.
Practical dbt: From Basics to Advanced
Build a stronger transformation workflow with modular models, testing, and real project discipline.
Apache Airflow: From Basics to Mastery
Understand DAGs, scheduling, and the operational mindset that separates toy pipelines from reliable ones.
Streaming Data with Apache Kafka
Build real-time pipelines that process events as they happen, not just in nightly batches.
Data Governance & Quality Standards
Set the strategy, ownership, and quality bar that keeps a data platform trustworthy at scale.