Learning path
A path through the data engineering stack: Python and pandas for processing, PostgreSQL for modelling and querying, Kafka for streaming events, then interview practice on Snowflake, SQL and system design.
- 7 steps
- 56 lesson days
- 137 interview questions
Who it's for
Developers and analysts who want to build data pipelines and platforms.
What you'll be able to do
- Process and transform data with Python and pandas
- Design schemas and write efficient SQL
- Stream events between systems with Kafka
- Explain warehouse and pipeline design in interviews
The path, step by step
- 1Course 14 days · ~30 min/day
Python
The glue language of data pipelines: scripts, APIs, file handling and automation.
Free, no sign-up - 2Course 14 days · ~30 min/day
Data Analysis with pandas
Transform and validate data in Python before loading it anywhere.
Free account - 3Course 14 days · ~30 min/day
PostgreSQL
Model data properly and write the SQL that pipelines and dashboards depend on.
Free account - 4Course 14 days · ~30 min/day
Apache Kafka
Move events between systems in real time: topics, partitions, consumer groups and reliable delivery.
Free account - 5Interview questions50 questions
SQL interview questions
Window functions, deduplication, gaps and islands: the SQL data engineering interviews love.
Free, no sign-up - 6Interview questions50 questions
Snowflake interview questions
The cloud warehouse many teams load data into: architecture, loading, performance and cost.
Free account - 7Interview questions37 questions
System Design interview questions
Design end-to-end systems: queues, partitioning, consistency and scaling.
Free account