Part 8: Data Engineering

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About Course

Data Engineering Complete Course

 

Module 1: SQL for Data Engineering

In this module, students will learn SQL from beginner to advanced level. They will start with fundamental queries such as SELECT, WHERE, GROUP BY, and JOIN, and gradually move to advanced concepts like Window Functions, CTE, Indexing, and query optimization. This module will also prepare students for real-world SQL interview questions and problem-solving scenarios required for data engineering roles.

 

Module 2: Big Data Processing with Apache Spark & PySpark

This module introduces distributed computing using Apache Spark and PySpark. Students will learn Spark architecture, cluster computing, schema management, data transformation, and performance optimization. They will also work with SparkSQL, Parquet files, and build scalable data processing workflows used in real big data environments.

 

Module 3: Cloud Data Engineering with Azure, Databricks & BI Integration

Students will learn how to build end-to-end cloud data pipelines using Azure Data Factory, Azure Data Lake, and Databricks. They will implement Medallion Architecture, perform data ingestion, transformation, and storage using Delta Lake, and connect processed data to Power BI for dashboard creation and business reporting.

 

Module 4: Data Transformation & Pipeline Development using DBT

This module focuses on modern data warehouse transformation using DBT and Snowflake. Students will learn to build scalable data models, implement data quality testing, manage Slowly Changing Dimensions, and orchestrate pipelines using tools like Dagster. They will also learn project documentation, monitoring, and production deployment practices.

 

Module 5: Advanced Data Engineering, Real-Time Processing & DevOps

In this final module, students will work on real-world end-to-end data engineering projects. They will learn real-time data processing using Spark Streaming and Kafka, implement CI/CD pipelines using Azure DevOps, manage data governance using Unity Catalog, and build production-ready automated data pipelines using Delta Live Tables and modern DevOps practices.

 

Course Features

Total Class – 20

Total Duration – 26 Hours

Total Quizzes – 5

Live Support and Solve Class

 

Verified Certificate after Course Completion

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What Will You Learn?

  • Write SQL queries for data analysis and data management
  • Perform advanced SQL operations like JOIN, CTE, and Window Functions
  • Process large-scale data using Apache Spark and PySpark
  • Build distributed data pipelines
  • Work with Azure Data Factory and Azure Data Lake
  • Implement modern data architecture (Medallion Architecture)
  • Transform and manage data using DBT and Snowflake
  • Perform real-time data processing using Spark Streaming
  • Build dashboards using Power BI
  • Deploy production-ready data pipelines
  • Implement CI/CD and DevOps in data engineering
  • Complete a real-world end-to-end data engineering project

Course Content

Module 00: Watch Class Preview Before Enrolment
Check out 3 Free Preview videos

Module 01: Course Materials and Paid Community Links
After enrolling this course, please download all the materials for this course

Module 02: SQL Preparation for Data Engineering

Module 03: Intro to Apache Spark and PySpark

Module 04: Databricks Project: Azure Data Factory

Module 05: Project with DBT

Module 06: Advanced Databricks এবং End-to-End প্রজেক্ট

Module 07: All Quizzes

Module 08: Completion and Feedback

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