IIQMC Data Engineering Career Accelerator

 🚀 Launch Your Career in Data Engineering with IIQMC! 📊

Welcome to the official page of the Data Engineering Career Accelerator Program by IIQMC (International Initiative for Quality Management & Computing) — designed to equip you with the skills and tools needed to thrive in the world of Big Data, Cloud, and Real-Time Analytics.

🔧 Learn industry-demanded technologies like Python, SQL, Spark, Airflow, Kafka, AWS, and Data Warehousing – all in one power-packed program.

📈 Whether you’re an aspiring data engineer, transitioning from software development, or aiming to master pipelines and ETL architecture — this course is your ultimate launchpad to a high-growth data career.

✅ Hands-on Projects

✅ Expert Mentorship

✅ Job-Ready Curriculum

✅ Certification & Career Support

📚 Join us and build the data infrastructure of tomorrow!

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🔷 Data Engineering Career Accelerator Program

Become a Job-Ready Data Engineer in 6 Months

🌟 Overview

The Data Engineering Career Accelerator by IIQMC (International Initiative for Quality Management & Computing) is an intensive, hands-on program crafted to help aspiring data professionals master the end-to-end data pipeline ecosystem. From data ingestion to transformation and deployment on the cloud, this course empowers you with real-world skills to land high-paying roles in data engineering.

📌 What You Will Learn

• Design and manage scalable data pipelines

• Work with structured and unstructured data

• Master ETL processes using modern tools

• Develop expertise in Apache Spark, Airflow, Kafka

• Implement cloud-based data platforms (AWS, GCP)

• Understand Data Warehousing, Lakehouse & Delta Lake

• Apply SQL, Python, and Shell scripting in projects

• Optimize performance, storage, and query efficiency

📚 Course Modules

✅ Beginner Level

1️⃣ Introduction to Data Engineering

 – Roles, Responsibilities & Career Paths

 – Overview of the Modern Data Stack

2️⃣ Linux & Shell Scripting for Data Engineers

 – Bash Scripting Basics

 – File Manipulation, Automation Tasks

3️⃣ SQL for Data Analysis & Transformation

 – Joins, CTEs, Subqueries, Window Functions

 – Writing Efficient Queries

4️⃣ Python for Data Engineering

 – Data Structures, Functions, File I/O

 – Pandas, NumPy, JSON, and APIs

✅ Intermediate Level

5️⃣ ETL Pipelines & Data Transformation

 – Batch vs Real-Time Processing

 – Building ETL Workflows with Python & SQL

6️⃣ Apache Airflow

 – DAGs, Scheduling, Sensors, Operators

 – Task Monitoring and Logging

7️⃣ Data Warehousing & Modeling

 – Star vs Snowflake Schema

 – Dimensional Modeling & Slowly Changing Dimensions

8️⃣ Apache Spark & Big Data Processing

 – PySpark Basics

 – Transformations, Actions, and DataFrames

✅ Advanced Level

9️⃣ Apache Kafka & Real-Time Streaming

 – Kafka Topics, Producers & Consumers

 – Stream Processing with Kafka & Spark

🔟 Cloud Data Engineering (AWS/GCP)

 – AWS S3, Redshift, Lambda, Glue

 – GCP BigQuery, Dataflow, Pub/Sub

1️⃣1️⃣ DataOps & CI/CD for Data Pipelines

 – Git, Docker, Jenkins

 – Testing and Monitoring Data Workflows

1️⃣2️⃣ Capstone Project

 – Build and deploy a complete data pipeline using cloud-native tools

 – Real-time data ingestion, transformation, warehousing, and visualization

🛠️ Hands-On Projects

• YouTube Data Ingestion Pipeline

• Real-Time Stock Market Feed with Kafka

• Sales Dashboard with Redshift and QuickSight

• ETL on COVID-19 Datasets using Airflow

• Data Lake implementation using Spark on AWS S3

🎯 Who Should Join?

• Freshers with programming knowledge

• Software engineers transitioning to data roles

• Analytics professionals looking to upskill

• IT professionals wanting to enter high-paying data careers

🎁 What’s Included

• 100+ Hours of Live Training

• 10+ Hands-on Projects

• 1 Capstone Project

• Mentor-led Doubt Sessions

• Resume Building & Mock Interviews

• Certification from IIQMC

📜 Certification

Upon successful completion, you will receive the IIQMC Certified Data Engineer Certificate – recognized by hiring partners and employers globally.