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Data Engineer Job Oriented Program

#No.1 Data Engineer Course

Prepzee’s Data Engineering Course has been curated to help you master skills like AWS Data Engineering, Databricks, Snowflake, DBT, Airflow and Kafka. This Data Engineering Bootcamp will help you get your dream Job in Data Engineering Domain.

  • Master AWS, Databricks, Snowflake, DBT & Airflow
  • 8+ Real world Project with 200GB of Datasets
  • Clear 4 Data Engineering Certifications (AWS, Databricks, Snowflake & DBT)

Download Curriculum
AWS Data Engineer Job Oriented Program
Featured In

What You will Learn in the Program?

  • Module 1

    Python for Data Engineering

    Live Training
    • Introduction to Python and environment setup
    • Running Python scripts and basic syntax
    • Variables and data types in Python
    • Working with lists, tuples, sets, and dictionaries
    • Conditional statements and control flow
    • Loops and functions in Python
    • Introduction to Python libraries
    • NumPy for numerical operations
    • Pandas for working with structured data
  • Module 2

    Data Engineering Essentials

    Live Training
    • Understanding Structured, Unstructured, and Semi-Structured
    • Properties of Data: Volume, Velocity, and Variety
    • Comparing Data Warehouses and Data Lakes
    • Managing and Orchestrating ETL Pipelines for Data Processing
    • Data Modeling, Data Lineage, and Schema Evolution
    • Optimizing Database Performance
  • Module 3

    Cloud Data Engineering with AWS

    Live Training
    • Cloud basics (IaaS, PaaS, SaaS) & AWS setup
    • Core services: IAM, EC2, S3 (Data Lake)
    • Data lake design & Medallion Architecture (Bronze, Silver, Gold)
    • Build ETL pipelines using AWS Glue (Catalog, Crawlers, Jobs)
    • Data warehousing with Amazon Redshift
    • Real-time streaming with Kinesis (Streams, Firehose)
    • Serverless processing using AWS Lambda
    • Query data using Amazon Athena
    • NoSQL basics with DynamoDB
    • Choosing the right tools (Kinesis vs Kafka, DynamoDB vs RDS vs S3)
  • Module 4

    Large-Scale Data Processing with Databricks

    Live Training
    • Introduction to Databricks and Spark execution
    • RDD overview and DataFrames for distributed processing
    • Reading and writing data (CSV, Parquet)
    • Data ingestion and transformation using PySpark
    • Spark SQL, joins, aggregations, and window functions
    • Performance optimization and monitoring using Spark UI
    • Azure Databricks architecture and cluster management
    • Unity Catalog for data governance and access control
    • Delta Lake architecture and working with Delta tables
    • Implementing Medallion architecture (Bronze, Silver, Gold)
    • Designing batch and real-time data pipelines
    • End-to-end data processing using Databricks
  • Module 5

    Snowflake with Cortex AI 🔥

    Live Training
    • Introduction to Snowflake
    • Introduction to Snowflake Cortex AI
    • Snowflake’s use cases in data engineering
    • Data types and structures in Snowflake
    • Snowflake architecture deep dive
    • Cloud services layer, compute layer, storage layer
    • Data storage and performance optimization
    • Loading data into Snowflake
    • Data transformation in Snowflake
    • Implementing real-time ETL pipelines using Snowflake
    • Connecting Snowflake to BI tools like Tableau, Power BI
    • Cortex AI
    • Cortex AI Search Service
    • Cortex Analyst
    • Document AI for NLP & predictive analytics
  • Module 6

    Airflow for Orchestration / Kafka for Streaming

    Live Training
    • Airflow Introduction
    • Different Components of Airflow
    • Installing Airflow
    • Understanding Airflow Web UI
    • DAG Operators & Tasks in Airflow Job
    • Create & Schedule Airflow Jobs For Data Processing
    • Create plugins to add functionalities to Apache Airflow
    • Core Concepts of Kafka
    • Kafka Architecture
    • Where is Kafka Used
    • Understanding the Components of Kafka Cluster
    • Configuring Kafka Cluster
  • Module 8

    Data Engineering for AI Systems 🤖

    Live Training
    • Understanding RAG Architecture from a Data Pipeline Perspective
    • How data flows from source systems → embeddings → vector database →LLM
    • Role of Data Engineers in building and maintaining RAG data pipelines
    • Vector Databases for Data Storage & Retrieval
    • Storing and managing embeddings as a new form of data storage
    • Processing and Managing Unstructured Data
    • Data Ingestion Strategies for AI Applications
    • Batch and streaming ingestion for AI systems
  • Module 9

    Interview/ Certification/ Resume Preparation

    Live Training
    • Get Mock Interview Sessions
    • Get guidance to show Projects & Experience in your resume
    • Get Sample Exam Papers for Certifications
    • Build ATS Friendly Resume for better Reach 
Download Syllabus

Data Engineer Classes Overview

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    100+ Hours of Live Training

    Including Top 2 Data Engineering Tools according to Linkedin Jobs

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    90+ Hours Hands-on & Exercises

    Learn by doing multiple labs in your data engineering online training journey

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    8+ Projects & Case Studies

    Get a feel of Data Engineering professionals by doing real-time projects.

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    24*7 Technical Support

    Call us, E-Mail us whenever you stuck.

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    Learn from the Top 1% of Experts

    Instructors are Microsoft Certified Trainers providing data engineer training.

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    Lifetime Live Training Access

    Attend multiple batches until you achieve your Dream Goal.

Total Program Fee
₹47,999
(*Incl. Taxes)
Pay In Installments, as low as
₹2,666/month

We have partnered with the following financing companies to provide competitive finance options at as low as 0% interest rates with no hidden cost.

Admission Closes on :
Apply Now

Learn Projects & Assignments Handpicked byIndustry Leaders

Our tutors are real business practitioners who hand-picked and created assignments and projects for you that you will encounter in real work.

Siddharth
Neeraj
Nagarjuna
Project 1 Implement a live data streaming pipeline using AWS Kinesis and Snowflake

A real-time data pipeline using AWS Kinesis and Snowflake to stream, process, and load data for instant analytics and business intelligence

Project 2 Design a Snowflake data pipeline using AWS Kinesis for ingestion and Airflow for orchestration

Designed a Snowflake data pipeline using AWS Kinesis for real-time ingestion and Apache Airflow for orchestration, enabling automated, scalable, and efficient data processing.

Project 3 Design an End to End ETL Pipeline on AWS EMR Cluster

Designed an end-to-end ETL pipeline on AWS EMR using Spark for processing, S3 for storage, and Hive for data warehousing and querying.

Project 4 Develop a comprehensive financial data pipeline with AWS and PySpark.

Developed a comprehensive financial data pipeline using AWS and PySpark to ingest, transform, and analyze large-scale financial data for real-time insights and reporting.

Project 5 Build an ETL Data Pipeline for Youtube Analytics

Built an ETL data pipeline for YouTube Analytics to extract video metrics via API, transform using Python, and load into a data warehouse for reporting.

That’s what They Said

  • Placed at Microsoft as a Data Engineer! The program gave me strong practical exposure to real-world data engineering workflows, hands-on projects, and guidance from industry professionals. It really helped me build the skills and confidence needed for this transition. Highly recommended for anyone serious about a career in Data Engineering.

    Kishan Yadav Data Engineer @ Microsoft

    Transitioned from traditional Big Data technologies into modern Data Engineering workflows with the help of this program. The practical learning approach, real-world projects, and exposure to new-age tools helped me strengthen my skills in modern data engineering. Highly recommended for professionals looking to upgrade from Big Data to cloud and modern Data Engineering technologies.

    Eresh Tayanna Senior Data Engineer @ Maveric Systems

    The Data Engineering program gave me strong practical exposure to real-world data engineering workflows, cloud technologies, and hands-on projects. The knowledge and experience I gained through the program helped me develop the skills and confidence required to secure this opportunity. Highly recommended for anyone serious about building a career in Data Engineering.

    Mayank Sharma Data Engineer @ Databricks

  • I had an excellent experience with Prepzee’s Data Engineer course. The content was well-structured, practical, and aligned with current industry requirements. The hands-on approach helped me understand real-world use cases effectively. A special thanks to Ajitesh, whose clear explanations, industry insights, and willingness to answer questions made the learning experience even more valuable.

    Manisha Kumari Data Engineer @ HCLTech

    The program helped me strengthen my expertise in modern AWS Data Engineering with a strong focus on practical implementation and real-world workflows. The hands-on projects, industry-oriented approach, and guidance from working professionals made the learning highly valuable. A great program for professionals looking to upskill in modern cloud and data engineering technologies.

    Kishor Azure Data Engineer @ Synechron

    I have completed the Data Engineering program with Prepzee, where I learned AWS, Snowflake, DBT, and Airflow. It was an amazing experience with a strong focus on practical learning. Special thanks to our trainer, Aneel, who provided great support during the lab sessions. Prepzee is the best platform for beginners who want to become experts in Data Engineering.

    Waqar Shareef Senior Data Analyst

  • Coming from a PostgreSQL DBA background, I wanted to expand my skills into modern Data Engineering. This program gave me hands-on experience with Azure, Databricks, Snowflake, Airflow, and real-world data engineering workflows. The practical projects and structured learning helped me understand cloud-based data platforms and strengthened my ability to contribute to data engineering initiatives.

    Jatin Garg DBA @ TCS

    Prepzee has been a great partner in upskilling employees. Their training content is well-structured, and the LMS recordings made it easy to review sessions anytime. The trainer was knowledgeable and always ready to help. I would highly recommend Prepzee to anyone looking to enhance their skills.

    Sheetal Katiyar Senior Module Lead @ Confidential

    After several years in software development, I wanted to transition into Data Engineering. This program provided hands-on experience with Azure, Databricks, Snowflake, Airflow, Kafka, and real-world projects. The practical learning approach helped me build industry-relevant skills and played a key role in my successful transition to a Data Engineer role and later growth into a Senior Data Engineer position.

    Vasantha Manvitha Bonda Data Engineer @ Cargill

Skills Covered

Tools Covered

Placement Overview

  • 500+
    Career Transitions
  • 9 Days
    Placement time
  • Upto 350%
    Salary hike

Corporate Training

Train your Employees with Customized Learning
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Data Engineer Program

Get Certified after completing Data Engineer full course with Prepzee

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Frequently Asked Questions

Enroll in our Data Engineer Job-Oriented Program and embark on a dynamic journey towards a thriving career in data engineering. This comprehensive program is designed to equip you with the skills and knowledge necessary to excel in the ever-evolving field of data engineering. Throughout this program, you'll delve into a diverse array of tools and technologies that are crucial for data engineers, including popular platforms like PySpark, AWS, and AWS Glue Analytics, Kafka , Airflow among many more.

Prepzee offers 24/7 support to resolve queries. You raise the issue with the support team at any time. You can also opt for email assistance for all your requests. If not, a one-on-one session can also be arranged with the team. This session is, however, only provided for six months starting from your course date.

All instructors at Prepzee are Amazon certified experts with over twelve years of experience relevant to the industry. They are rightfully the experts on the subject matter, given that they have been actively working in the domain as consultants. You can check out the sample videos to ease your doubts.

Prepzee provides active assistance for job placement to all candidates who have completed the training successfully. Additionally, we help candidates prepare for résumé and job interviews.

Projects included in the data engineer training program are updated and hold high relevance and value in the real world. Projects help you apply the acquired learning in real-world industry structures. Training involves several projects that test practical knowledge, understanding, and skills. High-tech domains like e-commerce, networking, marketing, insurance, banking, sales, etc., make for the subjects of the projects you will work on. After completing the Projects, your skills will be synonymous with months of meticulous industry experience.

Prepzee's Course Completion Certificate is awarded once the data engineer training program is completed, along with working on assignments, real-world projects, and quizzes, with a least 60 percent score in the qualifying exam.

Actually, no. Our job assistance program intends to help you land the job of your dreams. The program offers opportunities to explore competitive vacancies in the corporates and look for a job that pays well and matches your profile and skill set. The final hiring decision will always be based on how you perform in the interview and the recruiter's requirements.

You can enroll for AWS Data Engineer certification DEA C01 certification.

The course is designed to equip professionals with essential skills in cloud data engineering, making it ideal for IT professionals, DBAs, and data analysts. Through the AWS Data Engineer Training, participants gain hands-on experience with tools like AWS Glue, PySpark, Kafka, and Snowflake. This program prepares individuals for roles such as AWS Data Engineer, Cloud Data Engineer, and Data Integration Engineer.

The course is specifically designed to help you transition into a data engineering career by providing in-depth knowledge and hands-on experience in key technologies like PySpark, AWS Glue, Kafka, and Snowflake. Through the AWS Data Engineer course, you'll learn how to manage data pipelines, work with cloud architecture, and handle real-time data processing.

What makes this Data Engineering online training different from others is its focus on practical, hands-on experience with real-world projects and case studies. The course offers 100+ hours of live, instructor-led training and includes 24/7 technical support. With lifetime access to course materials and a focus on preparing you for certification exams, it ensures you're fully equipped to transition into a data engineering role with confidence.

Yes, you can definitely take data engineer certification course while working a full-time job. The Data Engineering Course is designed to be flexible, with weekend live sessions and self-paced learning materials. This allows you to balance your work commitments while gaining the skills needed for a career in data engineering. Plus, the lifetime access to course content lets you learn at your own pace.

From data engineer training, you will gain practical skills in designing and managing data pipelines, working with cloud-based data infrastructure, and processing large datasets efficiently. Through this data engineer online course You'll also learn how to implement data orchestration and automation, optimize database performance, and handle real-time data streams. Additionally, the hands-on projects will help you build proficiency in data integration, ETL processes, and using modern data engineering tools, preparing you for real-world scenarios in data engineering roles.

No, you don’t need a background in data science or software development to enroll. The data engineer certification course is designed to accommodate individuals from various technical backgrounds, including IT professionals, database administrators, and data analysts. It starts with foundational concepts and gradually progresses to more advanced topics, ensuring that anyone with basic programming and analytical skills can successfully transition into a data engineering role.

Yes, throughout the data engineer certification course, you’ll work on real-world datasets and projects to build practical experience. The Data Engineer Bootcamp focuses on hands-on learning, where you’ll tackle industry-relevant challenges and apply your skills to solve real data engineering problems. This ensures you’re not just learning theory but also gaining the experience needed for a career in data engineering.

Yes, the data engineer course primarily focuses on AWS as the cloud platform, providing in-depth training on AWS services like Glue, Kinesis, and Athena. While it doesn’t cover Google Cloud or Azure in detail, the skills gained are highly transferable to other cloud platforms.

Yes, coding exercises and hands-on labs are a key part of the data engineer certification training. You'll engage in practical exercises to build real-world data pipelines and work with cloud technologies, ensuring you gain hands-on experience throughout the course.

data engineer certification course is highly interactive, offering a blend of live instructor-led sessions and hands-on practice. You will have live sessions to engage with instructors, ask questions, and participate in discussions, ensuring a dynamic learning experience. Additionally, the Data Engineering training includes practical exercises and projects that reinforce your understanding, making it more engaging than just pre-recorded content.

Yes, data engineer certification course covers essential topics like data pipelines, ETL processes, and big data technologies. You’ll learn how to design, manage, and optimize data workflows, ensuring seamless data integration and transformation. By completing the course, you’ll be well-prepared for the Data Engineering certification, which will validate your skills in working with cloud-based data systems and big data technologies.

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