Building Scalable Data Pipelines
Design and implement large-scale data pipelines. Learn ETL/ELT patterns, Apache Spark, Kafka, data warehousing, and modern data stack technologies.
DVM
Dr. Vikram Mehta
AI Research Lead, Former Google
What You Will Learn
Design ETL and ELT architectures
Build data pipelines with Apache Spark
Stream processing with Kafka
Data warehouse design patterns
Implement data quality checks
Curriculum
1
ETL/ELT Patterns
25 min
•ETL vs ELT comparison
•Pipeline design patterns
•Data staging strategies
•Idempotency and fault tolerance
2
Apache Spark
30 min
3
Stream Processing
20 min
About the Instructor
DVM
Dr. Vikram Mehta
AI Research Lead, Former Google
PhD in Machine Learning from IIT Bombay. 7+ years training AI systems at Google and Microsoft. Holds 30+ published papers at top-tier conferences (NeurIPS, ICML, ACL). Now advises AI startups and mentors hundreds of engineers.
Prerequisites
Python or Scala experience
Understanding of distributed systems
Basic SQL knowledge
Familiarity with data concepts
Who Is This For
Data Engineers
Data Scientists
Database Administrators
Data Architects
What Is Included
Live session recording
Pipeline architecture templates
Spark code examples
Performance optimization guide
Data quality framework
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