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• date: 13 September 2026
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Real-World Data Engineering: Streaming & Cloud Projects
Last updated 9/2025
Created by Pianalytix • 97,000+ Students Worldwide
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All Levels | Genre: eLearning | Language: English + subtitle | Duration: 72 Lectures ( 7h 59m ) | Size: 7.7 GB

Build hands-on real-world data engineering projects using Kafka, Spark, Flink, Airflow, NiFi, PostgreSQL, and AWS.

What you'll learn
⚡ Build scalable data pipelines using Kafka, Spark, and Flink
⚡ Orchestrate workflows with Apache Airflow and NiFi
⚡ Manage and query data with PostgreSQL, HDFS, and AWS S3
⚡ Design real-time streaming pipelines for analytics and monitoring
⚡ Implement ETL processes for structured and unstructured data
⚡ Handle data ingestion, transformation, and storage at scale
⚡ Apply distributed computing techniques for big data workloads
⚡ Build portfolio-ready projects to showcase real-world engineering skills

Requirements
❗ Intermediate data engineering learners who know Python and SQL
❗ Familiarity with basic data engineering concepts (ETL, pipelines)

Description
Data engineering is one of the most in-demand skills in today's data-driven world, and the best way to master it is throughreal-world projects. This course is designed for learners who already have beginner-level skills in Python and SQL and are ready to step intointermediate data engineering workflows.

Throughout this course, you will work onpractical, end-to-end data engineering projects that cover a wide range of modern tools and platforms. You'll gain experience withstreaming technologies like Apache Kafka, Spark, and Flink, orchestration tools such asApache Airflow and NiFi, and storage systems includingPostgreSQL, HDFS, and AWS S3. These projects emphasize buildingscalable data pipelines, ETL workflows, real-time analytics, and cloud-based data solutions—skills that are highly relevant for professional data engineers.

The focus of the course is onapplied learning. Instead of only discussing concepts, you'll see how to bring them together into real workflows, giving you the confidence to handlebig data challenges in a production-like environment. Whether it's ingesting high-volume streaming data, orchestrating jobs, performing distributed computations, or leveraging AWS services for cloud analytics, you'll develop the hands-on skills needed to work in today's data engineering ecosystem.

By the end of this course, you will have built multipleportfolio-ready projects that showcase your ability to design, implement, and managedata pipelines, streaming systems, and analytics solutions. These projects will not only strengthen your technical knowledge but also demonstrate to employers that you can apply data engineering skills in practice.

This course is best suited for learners with some prior exposure to programming and databases, who are eager to grow intointermediate or advanced data engineering roles. If you're looking to sharpen your skills and build real, demonstrable experience, this course is the right step forward.

Who this course is for
⭐ Aspiring data engineers, analysts, and developers who want hands-on project experience using real-world tools and workflows in a complete data pipeline.

https://www.udemy.com/course/data-engineering-projects/

   
   
   

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