The Data Engineer's Encyclopedia

Master ETL & Data
Engineering — Everything,
In One Place

Definitions, architecture guides, tool deep-dives, code patterns, and interview prep for Python, Talend, DataStage, AWS Glue, ADF, Spark, and more.

Explore Tools →Interview PrepA–Z Glossary
200+Definitions
80+Interview Q&As
50+Tools Covered
15+Architecture Patterns
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// tools & platforms

Deep Dives by Tool

View all tools →
🐍

Python

Universal language of data pipelines

🔗

Talend

Enterprise ETL & data integration

🏗️

IBM DataStage

Enterprise-grade parallel ETL

⚡

AWS Glue

Serverless ETL on Amazon Cloud

🔷

Azure Data Factory

Microsoft cloud data integration

🔴

Oracle / ODI

Enterprise RDBMS & data integrator

🗄️

SQL Server / SSIS

Microsoft SQL & integration services

🔥

Apache Spark

Large-scale distributed processing

📐

dbt

SQL-first data transformation

// how it works

The Modern Data Pipeline

01
📥
Sources
APIs, DBs, Files, Streams
→
02
🔌
Ingestion
Fivetran, Airbyte, Debezium
→
03
🏊
Raw Layer
S3, ADLS, GCS Data Lake
→
04
⚙️
Transform
dbt, Spark, Glue, ADF
→
05
🏪
Serving
Snowflake, BigQuery, Redshift
→
06
📊
Consumers
BI, ML Models, APIs
// learn

Concepts & Guides

All concepts →
architecture8 min read

ETL vs ELT: Which Should You Use in 2026?

ingestion12 min read

Understanding Change Data Capture (CDC) Patterns

architecture10 min read

Data Lakehouse vs Data Warehouse: Complete Comparison

modeling15 min read

Slowly Changing Dimensions: Types 1, 2, 3 and 6 Explained

streaming20 min read

Apache Kafka Deep Dive for Data Engineers

transform14 min read

dbt Best Practices for Production Pipelines

// interview prep

Ready for Your Interview?

Tool-specific Q&As, system design questions, and behavioral prep — all in one place.

Python Interview QsTalend Interview QsAWS Glue Interview QsSpark Interview QsSQL Interview QsSystem Design
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