How to become a streaming data engineer

Companies can capitalize on their data if they process it as fast as they produce it. It's hard to find people with the skills and knowhow to do this well; those that can will reap the rewards.

If you want to gain this skill and be in the top 1%, join this session where you will learn how to build real-time data pipelines and stream processing in pure Python, including feature engineering, pre-computations, inference, and real-time machine learning.

All this is possible with Quix Streams, an open-source library that works with Kafka using pure Python. It's lightweight and has a beautiful and straightforward interface.

Don’t miss this great opportunity to learn how to become a streaming data engineer with one of the creators of Quix Streams, Tomas Neubauer.


WHO IS THIS WEBINAR FOR?

Data engineers, machine learning engineers and data scientists looking to be at the top of your game. Expand your knowledge and opportunities by learning what it takes to become a Streaming Data Engineer. 


SPEAKER BIO

Tomas Neubauer is a co-founder and the CTO at Quix, works as a technical authority for the engineering team and is responsible for the direction of the company across the full technical stack. He was previously technical lead at McLaren, where he led architecture uplift for Formula 1 racing real-time telemetry acquisition. He later led platform development outside motorsport, reusing the know-how he gained from racing.mas Neubauer (CTO @ Quix)