October 2024
Beginner to advanced
3h 40m
English
conference
Data Superstream: Becoming a Data Engineer
by Matt Housley, Andy Petrella, Eevamaija Virtanen, Adi Polak, Dunith Danushka, Colleen Tartow, Xinran Waibel, Holden Karau, Jowanza Joseph
Closed Captioning available in German, English, Spanish, French, Italian, Japanese, Korean, Portuguese (Portugal, Brazil), Chinese (Simplified), Chinese (Traditional)
Overview
Sponsored by Redpanda
This Superstream brings together an amazing slate of data industry experts and O’Reilly authors to enrich your professional journey with personal experiences, real-world insights, critical skills, and best practices. Whether you’re an experienced engineer looking to expand your knowledge of tools, technologies, and techniques, or you’re just considering the leap into a new career, you’ll come away from this conference with valuable new ideas and perspectives.
You’ll hear from Andy Petrella (author of Fundamentals of Data Observability) on the critical role of data engineers in maintaining data integrity to prevent misinformation and manipulation in the age of AI; Eevamaija Virtanen (founder of Helsinki Data Week) on getting a first job and building a career; Adi Polak (author of Scaling Machine Learning with Spark) on stream processing patterns and open source software; Dunith Danushka (senior developer advocate at Redpanda Data) on building composable data platforms; Colleen Tartow (field CTO at VAST Data) on her career journey from astrophysics to engineering leadership; Xinran Waibel (founder of the Data Engineer Things Community) on the path to becoming a senior engineer; Holden Karau (author of five O’Reilly books) on concrete applications of data engineering to healthcare; and Jowanza Joseph (author of Mastering Apache Pulsar) on applying generative AI to data engineering problems.
What you’ll learn and how you can apply it- Discover the key skills data engineers use to design, build, and maintain the infrastructure necessary for data generation, storage, and processing
- Learn why data quality and data governance are necessary to ensure that data is clean and compliant
- Get tips on building your career amidst the rapid changes brought on by generative AI
- You’re interested in transitioning to a career in data engineering.
- You’re a data professional who wants to discover skills gaps and upskill accordingly to move to the senior or staff level.
- You want to effectively approach the data lifecycle from ingestion to labeling to solving problems with machine learning.
- You want to better understand what work matters the most at every stage of your career and learn how to build the skills you need to support your journey.
Recommended follow-up:
- Read Fundamentals of Data Engineering (book)
- Watch Introduction to the Fundamentals of Data Engineering (on-demand course)
- Read Designing Data-Intensive Applications (book)
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