Real-world projects from industry experts
With real world projects and immersive content built in partnership with top tier companies, you’ll master the tech skills companies want.
Data Engineering is the foundation for the new world of Big Data. Enroll now to build production-ready data infrastructure, an essential skill for advancing your data career.
04Days07Hrs48Min34Sec
At 5-10 hrs/week
Get access to classroom immediately on enrollment
Learn to design data models, build data warehouses and data lakes, automate data pipelines, and work with massive datasets. At the end of the program, you’ll combine your new skills by completing a capstone project.
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.
With real world projects and immersive content built in partnership with top tier companies, you’ll master the tech skills companies want.
Our knowledgeable mentors guide your learning and are focused on answering your questions, motivating you and keeping you on track.
You’ll have access to Github portfolio review and LinkedIn profile optimization to help you advance your career and land a high-paying role.
Tailor a learning plan that fits your busy life. Learn at your own pace and reach your personal goals on the schedule that works best for you.
We provide services customized for your needs at every step of your learning journey to ensure your success.
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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.
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.
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.
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.
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.
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.
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