Pay as you go
- Maximum flexibility to learn at your own pace.
- Cancel anytime.
At 5-10 hrs/week
Get access to classroom immediately on enrollment
To be successful in this program, you should have intermediate Python and SQL skills.
Learn to create relational and NoSQL data models to fit the diverse needs of data consumers. Use ETL to build databases in PostgreSQL and Apache Cassandra.
Sharpen your data warehousing skills and deepen your understanding of data infrastructure. Create cloud-based data warehouses on Amazon Web Services (AWS).
Understand the big data ecosystem and how to use Spark to work with massive datasets. Store big data in a data lake and query it with Spark.
Schedule, automate, and monitor data pipelines using Apache Airflow. Run data quality checks, track data lineage, and work with data pipelines in production.
Combine what you've learned throughout the program to build your own data engineering portfolio project.
Developer Advocate at DataStax
Amanda is a developer Advocate for DataStax after spending the last 6 years as a Software Engineer on 4 different distributed databases. Her passion is bridging the gap between customers and engineering. She has degrees from University of Washington and Santa Clara University.
Staff Engineer at SpotHero
In his career as an engineer, Ben Goldberg has worked in fields ranging from Computer Vision to Natural Language Processing. At SpotHero, he founded and built out their Data Engineering team, using Airflow as one of the key technologies.
CEO at Novelari & Assistant Professor at Nile University
Sameh is the CEO of Novelari, lecturer at Nile University, and the American University in Cairo (AUC) where he lectured on security, distributed systems, software engineering, blockchain and BigData Engineering.
Data Engineer at Wolt
Olli works as a Data Engineer at Wolt. He has several years of experience on building and managing data pipelines on various data warehousing environments and has been a fan and active user of Apache Airflow since its first incarnations.
VP of Engineering at Insight
David is VP of Engineering at Insight where he enjoys breaking down difficult concepts and helping others learn data engineering. David has a PhD in Physics from UC Riverside.
Data Engineer at Split
Judit was formerly an instructor at Insight Data Science helping software engineers and academic coders transition to DE roles. Currently, she is a Data Engineer at Split where she works on the statistical engine of their full-stack experimentation platform.
As a data scientist, Juno built a recommendation engine to personalize online shopping experiences, computer vision and natural language processing models to analyze product data, and tools to generate insight into user behavior.
Pay as you go