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DATA / ENGINEERING LEARNING PATH

Learn Data Engineering
with a clear path.

Connect ingestion, storage, transformation, quality, and orchestration into dependable data systems.

Intermediate5 learning stages8 topics
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LEARNING PATH / 01

Data Engineering

BEGINNERADVANCED
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OverviewRoadmapPracticeProjectsInterview prepProgress
THE BIG PICTURE

What is Data Engineering?

Data engineering brings together practices for making data useful and dependable. This path builds from SQL and Python foundations into cloud platforms, orchestration, quality, and project delivery.

WHY LEARN THIS
  • Understand how data systems fit together
  • Practice dependable pipeline design
  • Connect technical choices to data users
PREREQUISITES
  • Curiosity about data systems
  • SQL or Python basics are helpful
LEARNING ROADMAP

A clear route from foundation to fluency

Explore Data Engineering through beginner, intermediate, and advanced learning levels. Topic status is illustrative demo progress only.

3 LEARNING LEVELS
01Beginner

Beginner

Build fluency with the core ideas and everyday building blocks.

02Intermediate

Intermediate

Combine concepts into reliable, useful workflows.

02Not Started

ETL and ELT

Plan extraction, transformation, and loading.

IntermediatePractice Interview
03Not Started

Cloud platforms

Place data workflows in cloud contexts.

IntermediatePractice Interview
03Advanced

Advanced

Reason about scale, trade-offs, security, and optimization.

01Not Started

Distributed processing

Scale transformation using distributed compute.

AdvancedPractice Interview
02Not Started

Data quality

Make quality expectations testable and visible.

AdvancedPractice Interview
03Not Started

Orchestration

Schedule, observe, and recover workflow execution.

AdvancedPractice Interview

Status labels are sample progress and are not linked to a user account.

TURN CONCEPTS INTO SKILL

Hands-on practice

Try focused learning activities that reinforce the Data Engineering concepts you have just explored.

01

Design a batch pipeline

Practice this skill
02

Add quality checks and monitoring

Practice this skill
APPLY WHAT YOU LEARN

Project ideas for Data Engineering

Use a project to connect technical concepts to a practical problem and its constraints.

Explore project guides
PROJECT IDEA / 01

Enterprise data pipeline

Demo project outline · Data Engineering learning application

Explore projects
PROJECT IDEA / 02

Cloud warehouse flow

Demo project outline · Data Engineering learning application

Explore projects
CONNECT LEARNING TO THE CONVERSATION

Data Engineering interview preparation

Review your understanding and practice explaining your choices in a clear, structured way.

Explain architecture and trade-offsPractice SQL and PythonDiscuss incidents and data quality
Data Engineering interview Explore scenarios
COMMON SCENARIOS TO CONSIDER
01

Late-arriving data

02

Schema evolution

03

Duplicate and missing records

YOUR FUTURE LEARNING DASHBOARD

See how the topics connect.

A real learner dashboard could track progress by topic and stage when user accounts are introduced.

Demo Progress · not user data
Data Engineering pathDEMO
Beginner0 / 2 explored
Intermediate0 / 3 explored
Advanced0 / 3 explored
0 completed0 in progress8 not started
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