Cloud and Distributed Data Engineering

This unit integrates distributed systems, cloud computing, and practical data engineering tools to prepare students for entry-level engineering work. Students apply concepts from distributed processing, file formats, cost optimization, SQL, data modeling, pipelines, Apache Spark, and system design while developing career-ready artifacts.

Learning Objectives

• Analyze trade-offs among distributed systems architectures, big data file formats, and processing frameworks to select appropriate solutions for specified data workloads
• Apply core cloud concepts, service and management models, and cost-optimization strategies to design a scalable, secure, and cost-effective data pipeline
• Demonstrate the ability to implement and optimize data transformations by writing SQL queries, creating data models, and developing a simple Apache Spark job within a pipeline
• Evaluate types of data engineering roles and career pathways and demonstrate readiness by producing a targeted resume/portfolio and a mock system-design case summary for an entry-level position