Why Data Engineers are like Super Mario 🍄 #dataengineering
The importance of the flow state - #dataengineering
The difference between data ingestion & extraction - Data Engineering Explained 🎓
My favorite function in #dataengineering !
Testing the new Personalized AI Assistant for my Data Engineering needs
Pro tip for anyone who wants to get into Data Engineering!
PySpark equals Databricks? #dataengineering
Cloud or local machine - which to choose? #dataengineering
How to get a Data Engineering job? Data Engineering Explained 🎓
What are the different database types? Data Engineering Explained 🎓
What is Data Engineering?
How Databricks Offers an Alternative to Amazon Redshift #dataengineering
You need these two fundamentals to kick off with Data Engineering!
Will AI replace Data Engineering jobs?
How to get a Data Engineering job at a fortune 500 company
Important advice for everyone thinking about a job transition into Data Engineering
What is ELT? Data Engineering Explained 🎓
What is ETL? Data Engineering Explained 🎓
How to simplify your Spark or Kafka setup!
There is more to consider than just data size #dataengineer
Explore alternatives to Data Engineering
Why platform & pipeline design is crucial for Software Engineers
Why Software Engineer vs Data Engineer makes no sense!
Observability Engineer vs Data Engineer?!
With AWS Data Engineers can do nothing wrong
Data Engineer Tip for Airflow Alternative
The Data Engineering Cookbook Is Growing!
Level up your Data Science skills with Docker!
How to switch your career to Data Engineering
Why Data Engineers and Data Scientists should learn API fundamentals
Don't limit yourself to ETL tools in your Data Engineering career
You'll burn in hell if you don't write tests! Annoying Topics 12: #datascience #dataengineering
It's never simple! Annoying Topics Part 11: #datascience #dataengineering #dataengineer #bigdata
Unexpected New Features. Annoying Topics Part 10! #datascience #dataengineering #bigdata
You never have enough time or people to do the work! Annoying topics 9 #datascience #dataengineering
Using the data lake as a garbage dump! Annoying topics 8: data swamp #datascience #dataengineering
Access permissions driving me crazy! Annoying topics part 7 #datascience #dataengineering #bigdata
GDPR is the worst! Annoying topics part 6: GDPR #datascience #dataengineering #bigdata #gdpr
Good Engineering costs money! Annoying part 5: Costs #datascience #dataengineering
Dependency Management is Super Annoying! Annoying Topics 6 #datascience #dataengineering #bigdata
Most annoying topics for Data Engineers Part #3: API Changes #dataengineer #dataengineering
Most annoying topics for Data Engineers Part #2: Stuck Data Pipelines!
Most annoying topics for Data Engineers Part #1: Log Files!
Where are the Junior Data Engineer positions? Here what to can do:
Hadoop is not important anymore! Here's what to learn:
Data Scientists should learn Data Engineering! Here why:
Data Scientist or Data Engineer? A simple way to decide which path you should follow
The Two Fundamental Skills For Data Engineers. Plus how to get into Data Engineering as a Analyst
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About
Hi my name is Andreas Kretz. I teach Data Engineering at LearnDataEngineering.com. My Academy at learn data engineering will tech you everything to become a Data Engineer or use Data Engineering in your current job.
On this channel I talk about tools, techniques and topics that I experience in my day to day work.
As an Engineer you figure out how to ingest, process and store data to enable Data Scientists, Analysts or customers to do awesome stuff. Using tools like AWS, GCP, Apache Spark Apache Kafka, MongoDB, Python, Databricks, Apache Airflow and many more.
That's what data engineering, the plumbing of data science is all about.
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