Eduardo Mota
Sr. Cloud Data Architect
Data Lakes and Lakehouses on AWS
Learn how to manage raw and semi-structured data at scale using AWS data lakes and lakehouses. Ingest data into S3, register schemas with Glue Data Catalog, and query data flexibly with Athena. Process large datasets using Spark to transform, clean, and aggregate data for analytics. Implement lakehouse tables with Iceberg to combine the flexibility of data lakes with the structure of data warehouses. Support schema evolution and ensure data remains queryable as requirements change.
- Course
- Intermediate
- 15 hours
- Updated: May 13, 2026
Subscription · Monthly
- Cancel Anytime
- Unlimited access to hundreds of top-rated courses
- Hands-on projects with expert feedback
- Personalized career coaching and interview prep
- Program Certificates
Skills you'll learn
12 skills
- AWS data lakes
- ELT
- Big data fluency
- Data wrangling
- Amazon s3
Prerequisites
4 prerequisites
Prior to enrolling, you should have the following knowledge:
You will also need to be able to communicate fluently and professionally in written and spoken English.
Course Outline
- 5 lessons
- 1 project
Program Instructors
1 instructor
Unlike typical professors, our instructors come from Fortune 500 and Global 2000 companies and have demonstrated leadership and expertise in their professions:
Eduardo Mota
Sr. Cloud Data Architect
Subscription · Monthly
- Cancel Anytime
- Unlimited access to hundreds of top-rated courses
- Hands-on projects with expert feedback
- Personalized career coaching and interview prep
- Program Certificates