The $500k+ Data Engineering Roadmap: Exact Study Plan & Resources
Description
Start your Data Engineering journey w/ DataCamp here: Associate Data Engineer In SQL: https://datacamp.pxf.io/mOkAPa Industry Recognized Data Engineer Certification: https://datacamp.pxf.io/POqXMX Please note I may earn a small commission for any purchase through these links - Thank you for supporting the channel! ____________________________________________ This video is a Complete Data Engineering Roadmap — built for beginners, career switchers, and professionals who want to go from zero to job-ready in one structured path My Social Media Handles: LinkedIn: https://www.linkedin.com/in/afaque-ahmad-5a5847129/ YouTube Channel: https://www.youtube.com/@afaqueahmad7117 Playlists: Interview Preparation: https://www.youtube.com/playlist?list=PLWAuYt0wgRcKtqUhfVbtPjULMdYq5drs8 Spark Performance Tuning: https://www.youtube.com/playlist?list=PLWAuYt0wgRcLCtWzUxNg4BjnYlCZNEVth Github: https://github.com/afaqueahmad7117 Spark Performance Tuning Codes: https://github.com/afaqueahmad7117/spark-experiments Chapters: 00:00 - Why Data Engineering Is Critical for AI 01:22 - Topics 02:00 - Programming Languages 03:20 - Resources for Learning Python 03:56 - Video Resources for Le…
Description from YouTube. Full content on the video page.
More from Afaque Ahmad
TutorialsMastering Joins In Apache Spark: Complete Deep Dive
The video provides a deep dive into four Apache Spark physical join strategies: Sort Merge Join, Broadcast Hash Join, Shuffle Hash Join, and Broadcast Nested Loop Join. For each join, it explains the conditions for Spark's selection, visualizes its step-by-step internal mechanics, and demonstrates its appearance in Spark's physical plan and UI.
CommunityHow I Mastered System Design Interviews
This video teaches a six-step framework for mastering data engineering system design interviews, covering requirements gathering, pipeline design, data modeling, storage and file formats, data quality and observability, and pipeline resilience. It demonstrates how to apply this framework with practical examples and back-of-the-envelope calculations to justify design choices.
TutorialsDatabricks End-To-End Project | Zero-To-Expert | Streaming, AI, Lakeflow, Unity Catalog, AI/BI
This video demonstrates building an end-to-end restaurant analytics platform on Databricks, covering streaming and batch data ingestion, AI-powered sentiment analysis, and dashboard creation. It teaches how to use Unity Catalog, Lake Flow Connect for CDC, Spark declarative pipelines for real-time data from Event Hub, and how to construct a medallion architecture with fact and dimension tables.
CommunityHow Much DSA Do You Need To Crack Data Engineering Interviews?
Data engineers need to understand DSA concepts at an easy to medium level, focusing on practical applications like Big O intuition, arrays, hashmaps, and basic trees/graphs, rather than advanced algorithms. The video provides a practical DSA roadmap, differentiating between "must-knows," "good-to-knows" for stronger product/infra roles, and "overkill" topics for most classic data engineering interviews.
CommunityWill AI REPLACE Data Engineers?
AI will not replace data engineers, but it will shift their role from typing code to designing solutions, guiding AI tools, and verifying outputs. Data engineers should focus on core coding fundamentals, system and product thinking, and effectively using AI and other tools.
CommunityApache Spark Was Hard Until I Learned These 30 Concepts!
The video explains 30 key Apache Spark concepts, starting with a comparison to MapReduce to highlight Spark's in-memory processing and DAG-based execution model. It then details Spark's cluster architecture, job execution flow (driver, executors, tasks), and memory management within executor containers.