Scalable Systems and Career Readiness

This capstone unit integrates distributed systems, cloud computing, big data storage and processing, and core data engineering tools to prepare students for real-world data engineering tasks. It synthesizes technical system design and hands-on pipeline work with career-focused guidance to transition students from classroom knowledge to entry-level roles.

Learning Objectives

• Analyze distributed systems concepts, cloud service and management models, and cost-optimization strategies to recommend appropriate architectures for given big data scenarios
• Apply SQL, data modeling principles, and Apache Spark basics to design and implement end-to-end data pipelines that process and store large datasets using suitable file formats
• Demonstrate system design skills by producing a scalable, fault-tolerant deployment plan that specifies storage formats, processing engines, and operational considerations for distributed data processing
• Evaluate types of data engineering roles and create a targeted roadmap (including resume/portfolio items and interview strategies) to pursue an entry-level data engineering position