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Data Engineering Course

This Data Engineering course in association with MITx MicroMasters is designed by top domain experts to help you master core Data Engineering skills like Python, SQL, AWS, Spark, Kafka, etc. through multiple Data Engineering courses & real-time projects. Learn from top faculty at MIT & get MITxMicroMasters certified.

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Upskill for Your Dream Job

Learning Format

Online Bootcamp

Live Classes

7 Months

Career Services

by Intellipaat

MITxMicroMasters

Certification

500+

Hiring Partners

Process Advisors

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*Subject to Terms and Condition

Data Engineering Course Overview

Our Data Engineering course will provide you in-depth knowledge in SQL, Python, data pipelines, data transformation, Spark, and cloud services of AWS and Azure. Multiple Data Engineering courses and real-world projects help you master core concepts & skills like creating production-ready ETL and pulling data from multiple data sources, building cloud data warehouses, Data Modeling, etc.

Data Engineer Course Key Highlights

Career Guidance
7 Months of Live Sessions by Industry Experts
200 Hrs of Self-paced Videos
One-on-One with Industry Mentors
24*7 Support
50+ Industry Projects & Case Studies
Integrated with MITxMicroMasters
E-learning Videos from MIT faculty
Flexible Schedule
Lifetime Free Upgrade
Soft Skills Essential Training
Dedicated Learning Management Team

Free Career Counselling

We are happy to help you 24/7

About MIT and MIT IDSS

The Institute for Data, Systems, and Society (IDSS) is a cross-disciplinary unit made up of faculty from across the Massachusetts Institute of Technology (MIT). IDSS advances education and research in data analysis, statistics, and machine learning, and applies these tools in collaboration with social scientists, community, and policymakers to address complex societal challenges.

On the completion of this Data Engineer certification program, you will:

  • Receive an industry-recognized Certification in Data Engineering from Intellipaat.
  • Receive a course completion certification by MITxMicromasters on the completion of the modules by MIT.

To know more about the MIT IDSS, click here

Note: All certificate images are for illustrative purposes only and may be subject to change at the discretion of the MITx.

Career Transition

57% Average Salary Hike

$1,28,000 Highest Salary

12000+ Career Transitions

300+ Hiring Partners

Career Transition Handbook

*Past record is no guarantee of future job prospects

Who Can Apply for the Data Engineering Course?

  • Freshers and Undergraduates willing to pursue a career in data engineering
  • Anyone looking for a career transition to data engineering
  • IT Professionals
  • Experienced Professionals willing to learn data engineering
  • Technical and Nontechnical Professionals with basic-level programming knowledge can also apply
  • Project Managers
Who can aaply

What Roles does a Data Engineer Play?

Big Data Engineer

They design and build complex data pipelines and have expert knowledge in coding using Python, etc. These professionals collaborate and work closely with data scientists to run the code using various tools such as the Hadoop ecosystem, etc.

Data Architect

They are typically the database administrators and are responsible for data management. These professionals have in-depth knowledge in databases, and they also help in business operations.

Business Intelligence Engineer

They are skilled in data warehousing and create dimension models for loading data for large scale enterprise reporting solutions. These professionals are experts in using ELT tools and SQL.

Data Warehouse Engineer

They are responsible for looking after the ETL processes, performance administration, dimensional design, etc. These professionals take care of the full back-end development and dimensional design of the table structure.

Technical Architect

They design and define the overall structure of a system with an aim to improve the business of an organization. The job role of these professionals involves breaking large projects into manageable pieces.

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Skills to Master

SQL

No SQL (MongoDB)

Data Warehousing

OLAP

OLTP

ETL

Python Programming

Hadoop

Spark

Spark Streaming

AWS

Redshift

RDS

EMR

Apache Airflow

S3

S3 Glacier

Glue

Docker

Kubernetes

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Tools to Master

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Data Engineer Training Curriculum

Live Course Self Paced

Python 

  • Introduction to Python and IDEs – The basics of the python programming language, how you can use various IDEs for python development like Jupyter, Pycharm, etc. 
  • Python Basics – Variables, Data Types, Loops, Conditional Statements, functions, decorators, lambda functions, file handling, exception handling ,etc.
  • Object Oriented Programming – Introduction to OOPs concepts like classes, objects, inheritance, abstraction, polymorphism, encapsulation, etc.
  • Hands-on Sessions And Assignments for Practice – The culmination of all the above concepts with real-world problem statements for better understanding. 

SQL Basics – 

  • Fundamentals of Structured Query Language
  • SQL Tables, Joins, Variables 

Advanced SQL –  

  • SQL Functions, Subqueries, Rules, Views
  • Nested Queries, string functions, pattern matching
  • Mathematical functions, Date-time functions, etc. 

Deep Dive into User Defined Functions

  • Types of UDFs, Inline table value, multi-statement table. 
  • Stored procedures, rank function, triggers, etc. 

SQL Optimization and Performance

  • Record grouping, searching, sorting, etc. 
  • Clustered indexes, common table expressions.

Hands-on exercise: 

Writing comparison data between past year to present year with respect to top products, ignoring the redundant/junk data, identifying the meaningful data,  and identifying the demand in the future(using complex subqueries, functions, pattern matching concepts).

  • What is Data Engineering, Use Cases, and Applications?
  • Data Engineer or Data Scientist?
  • Data Engineering Problems
  • Tools of a Data Engineer
  • Working with Different Databases
  • Processing Tasks, Scheduling Tools, and Different Cloud Providers
  • Why Cloud Computing, Use Cases, and Applications?
  • Different Cloud Services

Learn the big data ecosystem and Apache Spark to load large volumes of data. Work with Spark SQL for querying data and optimizing the same. Build an ETL pipeline to pull the data from different data sources, such as HDFS and S3, and use different format data files, such as csv, txt, json, fixed format, streaming data, etc., to load the data. Work on Spark Cluster using AWS.

  • Introduction to HDFS and Apache Spark
  • Spark Basics
  • Working with RDDs in Spark
  • Aggregating Data with Pair RDDs
  • Writing and Deploying Spark Applications
  • Parallel Processing
  • Spark RDD Persistence
  • Integrating Apache Flume and Apache Kafka
  • Spark Streaming
  • Improving Spark Performance
  • Spark SQL and Data Frames
  • Scheduling or Partitioning
  • Understand the difference between SQL and NoSQL. Create relations data models and NoSQL-based data models on business reporting requirements. Work with ETL tools to push the data to the model.
  • Work on MS SQL and Mongodb for creating databases and using ETL tools for data extracting, transformation, and loading to the models.

Project 1: Data Modeling using Relational Databases

Create a dimensional model with dimension and fact tables. Create database and ETL for data transformation and loading into the dimensional model created. Optimize the ETL process for faster loading of data.

Project 2: Data Modeling using Apache Mongodb

Create NoSQL database and ETL for data transformation and data loading. Model your data in Apache Mongodb as per reporting requirements.

Master the skills of building a highly scalable data warehouse on AWS. Work with Redshift and pull the data from RDS and other media services of AWS using ETL pipeline and load the data into the data warehouse.

  • What is ETL, Use Cases, and Applications?
  • Why We Need ETL Tools>
  • Working with Different Data Sources—Relational Databases, NoSQL, HDFS, Stream Data, CSV Files, TXT Files, Json or XML Files, and Fixed File Formats
  • Transformation of Data
  • Loading Data into a Data Model or File System
  • Using SQL for Data Transformation
  • Optimizing ETL Processes
  • Understanding ETL Architecture for Tracking the Data Flow and Data Pipelines
  • Understanding Data Quality Checks

Master the skills of building a highly scalable data warehouse on AWS. Work with Redshift and pull the data from RDS and other media services of AWS using ETL pipeline and load the data into the data warehouse.

  • AWS Data Storage Services—S3, S3 Glacier, Amazon DynamoDB
  • AWS Processing Services—AWS EMR, EMR Cluster, Hadoop, Hue with EMR, Spark with EMR, AWS Lambda, HCatalog, Glue, and Glue Lab
  • AWS Data Analysis Services—Amazon Redshift, Tuning Query Performance, Amazon ML, Amazon Athena, Amazon Elasticsearch, and ES Domain

Learn to schedule, automate, and monitor ETL pipelines with Apache Airflow. Learn and master how to implement data quality checks and processes for running the ETL in a production environment. Understand and create a strong process and architecture to avoid ETL failure due to data quality issues. Learn how to handle ETL failure issues in a production environment.

  • Use Docker for converting your applications and data pipelines to containers-based applications
  • Orchestrate containers to deliver scalable and reliable performance using Kubernetes

Implement the concepts learnt in the program and create a highly scalable data warehouse architecture for loading data from different sources and use NoSQL database for query to provide data results asked by the analytics team. Use AWS cluster to deploy your solution data processing.

  • Non-Relational Data Stores and Azure Data Lake Storage
  • Data Lake and Azure Cosmos DB
  • Relational Data Stores
  • Why Azure SQL?
  • Azure Batch
  • Azure Data Factory
  • Azure Data Bricks
  • Azure Stream Analytics
  • Monitoring & Security
  • Introduction to Linux  – Establishing the fundamental knowledge of how linux works and how you can begin with Linux OS.
  • Linux Basics – File Handling, data extraction, etc.
  • Hands-on Sessions And Assignments for Practice – Strategically curated problem statements for you to start with Linux.
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Program Highlights

Live Session across 7 months
1:1 Industry Mentorship
50+ Industry Projects & Case Studies
24*7 Support

Interested in This Program? Secure your spot now.

The application is free and takes only 5 minutes to complete.

Reviews

4.8

Hear From Our Hiring Partners

Career Services By Intellipaat

Career Services

Career Oriented Sessions

Throughout the course

Over 20+ live interactive sessions with an industry expert to gain knowledge and experience on how to build skills that are expected by hiring managers. These will be guided sessions and that will help you stay on track with your up skilling objective.

Resume & LinkedIn Profile Building

After 70% of course completion

Get assistance in creating a world-class resume & Linkedin Profile from our career services team and learn how to grab the attention of the hiring manager at profile shortlisting stage

Mock Interview Preparation

After 80% of the course completion.

Students will go through a number of mock interviews conducted by technical experts who will then offer tips and constructive feedback for reference and improvement.

1 on 1 Career Mentoring Sessions

After 90% of the course completion

Attend one-on-one sessions with career mentors on how to develop the required skills and attitude to secure a dream job based on a learners’ educational background, past experience, and future career aspirations.

3 Guaranteed Interviews

After 80% of the course completion

Guaranteed 3 job interviews upon submission of projects and assignments. Get interviewed by our 400+ hiring partners.

Access to Intellipaat Job Portal

For 6 Months after Course Completion

Exclusive access to our dedicated job portal to apply for jobs. More than 400 hiring partners, including leading startups and product companies, are hiring our learners. Mentored support on job search and relevant jobs for your career growth.

Our Alumni Works At

Master Client Desktop

Peer Learning

Via Intellipaat PeerChat, you can interact with your peers across all classes and batches and even our alumni. Collaborate on projects, share job referrals & interview experiences, compete with the best, make new friends – the possibilities are endless and our community has something for everyone!

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Admission Details

The application process consists of three simple steps. An offer of admission will be made to selected candidates based on the feedback from the interview panel. The selected candidates will be notified over email and phone, and they can block their seats through the payment of the admission fee.

Submit Application

Submit Application

Tell us a bit about yourself and why you want to join this program

Application Review

Application Review

An admission panel will shortlist candidates based on their application

Admission

Application Review

Selected candidates will be notified within 3 days

Program Fee

Total Admission Fee

$ 2,632

Upcoming Application Deadline 3rd June 2023

Admissions are closed once the requisite number of participants enroll for the upcoming cohort. Apply early to secure your seat.

Program Cohorts

Next Cohorts

Date Time Batch Type
Program Induction 3rd June 2023 08:00 PM IST Weekend (Sat-Sun)
Regular Classes 3rd June 2023 08:00 PM IST Weekend (Sat-Sun)

Data Engineer Training FAQs

What courses are included in this Data Engineering course?

In this Data Engineer PG program, you will learn multiple Data Engineering courses along with case studies and project work.

Online Instructor-led:

Course 1: Preparatory Sessions — Python and Linux
Course 2: Data Wrangling with SQL
Course 3: Introduction to Data Engineering
Course 4: Big Data Engineering with Apache Spark and Kafka
Course 5: Data Modeling
Course 6: Cloud Data Warehouses
Course 7: Mastering ETL Tool — Informatica
Course 8: Data Engineering on the Cloud
Course 9: Schedule and Automate Data Pipelines with Apache Airflow
Course 10: Data Virtualization and Containerization
Course 11: Capstone Project

At the end of the course you will master the concepts and skills by working on Capstone Projects.

Apart from the live classes, you will have electives in a self-paced format:

Azure Data Factory

Intellipaat’s online Data Engineering courses will validate your skills in the domain and will add value to your resume. The real-life practical applications will help you develop a strong skill set that you can showcase to recruiters. Get the best Data Engineer certification course and excel in your data engineering career.

Data engineering can be called a branch of data science that involves preparing the data to be analyzed by data scientists and data analysts. This online Data Engineer training course includes practically applying data collection techniques and maintaining the organization’s data pipeline systems.

Intellipaat provides career services that include 1:1 mentorship to all the learners enrolled in this top online certification training course. MIT is not responsible for placements and career services.

On the completion of the Data Engineering online course, and the completion of the various projects and assignments in this program, you will receive your certification.

According to Glassdoor, the average annual salary of a certified data engineer in India is ₹850,000.

No, there are no assessments to be performed by you to take up this top Data Engineering course. Anyone who is passionate about learning data engineering and big data engineering is welcome to join our best online courses.

It is recommended that you have a basic level of knowledge in programming or any object-oriented coding language to better understand the Data Engineering concepts.

The top companies hiring data engineers around the globe are as follows:

  • Tata Consultancy Services (TCS)
  • LTI
  • Accenture
  • IBM
  • Amazon
  • Infosys
  • Capgemini

Yes, you can easily join the Data Engineering courses even if you do not have technical experience or are not from a technical background. However, having knowledge of any object-oriented programming language will be helpful.

The Data Engineering courses come with a duration of six months of live classes and lifelong access to course material. In this tenure, it is suggested that you devote six to seven hours a week to master the Data Engineering concepts taught in the online classes.

Due to the increase in the adoption of digital transformation by companies, domains like data engineering are top in demand. Currently there is a shortage of supply of data engineers and their demand is increasing. Due to this, companies are ready to offer high salaries to the right candidates. Hence, this Data Engineering domain definitely has a bright future.

Intellipaat provides career guidance services such as interview preparatory sessions, industry mentorship and more for all learners enrolled in the Data Engineering courses. MIT is not responsible for placements and career services.

You can expect a salary range of Rs.7-8 lakhs from the job offer. However it totally depends on how you perform in your interview. We have seen our learners achieving up to 30 LPA in salary packages.

We value the candidates who wish to learn but do not have the financial bandwidth to make an upfront payment of the fees. Hence, Intellipaat offers easy No Cost e.m.i option to the candidates.

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What is included in this course?

  • Non-biased career guidance
  • Counselling based on your skills and preference
  • No repetitive calls, only as per convenience
  • Rigorous curriculum designed by industry experts
  • Complete this program while you work

I’m Interested in This Program

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