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Data Engineer Job Oriented Program

#No.1 Data Engineer Course

Prepzee’s AWS Data Engineering Course has been curated to help you master skills like PySpark, AWS Data Engineer Certification DEA C01, AWS Glue, Kinesis, Airflow, Kafka and Snowflake. This AWS Data Engineering certification course will help you get your dream Job in Data Engineering Domain.

  • Master Data Engineer with AWS, Airflow, Kafka, Snowflake.
  • Hands-On PySpark Training for Data Engineering
  • Clear AWS Data Engineer Certification DEA C01

Download Curriculum
AWS Data Engineer Job Oriented Program
Featured In

What You will Learn in the Program?

  • Module 1

    SQL Fundamentals

    Recorded Session
    • SQL Basics and Data Retrieval
    • Aggregation and Grouping
    • Joins and Data Relationships
    • Data Manipulation and Transactions
    • Advanced SQL Functions and Conditional Logic
    • Window Functions and Ranking
    • Data Definition and Schema Management
    • Views, Stored Procedures, and Functions
    • Performance Optimization and Real-World Scenarios
  • Module 2

    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 3

    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 4

    Data Engineering for Real World & Certification

    Live Training
    • Cloud Computing Introduction
    • Understand IAAS, PAAS, SAAS
    • AWS Account Setup & Configuration
    • Build a Strong Foundation with IAM, EC2, EBS
    • Work on Amazon S3 (Data Lake) to Store Structured, Unstructured & real time data
    • Understand How Medallion Architecture work at Storage Layer in ETL/ELT
    • Deep understanding of Bronze, Silver & Gold Layer
    • Design ETL Pipelines using Amazon Glue
    • Work on Glue Data Catalog, Crawlers, Glue Jobs
    • Build Use Cases (ETL, data cataloging, job orchestration)
    • Use Redshift as a Data Warehouse for data engineering Projects
    • Creating Database, Schemas & Users
    • Loading Data into Redshift
    • Setting up Redshift for Data Engineering Projects
    • Handle Real-Time Streaming data with AWS Kinesis
    • How to Select between Kinesis & Kafka for Streaming Pipelines
    • Kinesis Data Streams, Firehose
    • Introduction to AWS Lambda
    • Creating and Deploying Lambda Functions
    • Event Sources and Triggers
    • Monitoring and Debugging Lambda Functions
    • Introduction to Amazon Athena
    • Understand Athena as a Serverless Query Service
    • Querying Data to analyse Structured, Semi Structured data
    • Introduction to DynamoDB
    • DynamoDB vs RDS vs S3
    • Reading and Writing Data
  • Module 5

    PySpark/ Databricks

    Live Training
    • Introduction to DataBricks
    • SparkSession
    • Understand RDD
    • Dataframes and its creation
    • Data sources (using CSV and Parquet) and
    • dataframe reader
    • Data targets and Dataframe writer
    • Spark SQL in PySpark
    • Spark UI
    • Databricks Architecture Overview
    • Databricks cluster pool
    • Understand Delta lake architecture
    • Work on Delta lake tables on Databricks
    • Ingestion, Transformation in Databricks
    • Work with DataFrames in Databricks
  • Module 6

    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 7

    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 AirflowCore 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

AWS 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 AWS data engineering online training journey

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    8+ Projects & Case Studies

    Get a feel of AWS 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 AWS data engineer training.

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    Lifetime Live Training Access

    Attend multiple batches until you achieve your Dream Goal.

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

  • Stam Senior Cloud Engineer at AWS
    Amit Sharma Manager at Visa

    Enrolling in the AWS Data Engineer Job Oriented Program by Prepzee for the AWS Data Engineer certification (DEA C01) was transformative. The curriculum covered critical tools like PySpark, Python, Airflow, Kafka, and Snowflake, offering a complete understanding of cloud data engineering. The hands-on labs solidified my skills, making complex concepts easy to grasp. With a perfect balance between theory and practice, I now feel confident in applying these technologies in real-world projects. Prepzee's focus on industry-relevant education was invaluable, and I’m grateful for the expertise gained from industry professionals.

    Kashmira Palkar Manager - Deloitte
  • Abhishek Pareek Technical Manager Capgemini.

    I enrolled in the DevOps Program at Prepzee with a focus on tools like Kubernetes, Terraform, Git, and Jenkins. This comprehensive course provided valuable resources and hands-on labs, enabling me to efficiently manage my DevOps projects. The insights gained were instrumental in leading my team and streamlining workflows. The program's balance between theory and practice enhanced my understanding of these critical tools. Additionally, the support team’s responsiveness made the learning experience smooth and enjoyable. I highly recommend the DevOps Program for anyone aiming to master these essential technologies.

    Nishant Jain Senior DevOps engineer at Encora
    Vishal Purohit Product Manager at Icertis

  • Enrolling in the Data Engineer Job Oriented Program at Prepzee,, exceeded my expectations. The course materials were insightful and provided a clear roadmap for mastering these tools. The instructors' expertise and interactive learning elements made complex concepts easy to grasp. This program has been invaluable for my professional growth, giving me the confidence to apply these technologies effectively in real-world projects.

    Abhishaily Srivastva Product Manager - Amazon

    Enrolling in the Data Analyst Job Oriented Program at Prepzee, covering Python, SQL, Advanced Excel, and Power BI, was exactly what I needed for my career. The course content was well-structured and comprehensive, catering to both beginners and experienced learners. The hands-on labs helped reinforce key concepts, while the Prepzee team’s support was outstanding, always responsive and ready to help resolve any issues.

    Komal Agarwal Manager EY

    Prepzee has been a great partner for us and is committed towards upskilling our employee.Their catalog of training content covers a wide range of digital domains and functions, which we appreciate.The best part was there LMS on which videos were posted online for you to review if you missed anything during the class.I would recommend Prepzee to all to boost his/her learning.The trainer was also very knowledgeable and ready to answer individual questions.

    Shruti Tawde HR at JM Financial Services Ltd

Skills Covered

Tools Covered

Placement Overview

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

Corporate Training

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AWS Data Engineer Program

Get Certified after completing AWS Data Engineer full course with Prepzee

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Frequently Asked Questions

Enroll in our AWS 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 aws 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 aws 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 AWS 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 aws data engineer certification course while working a full-time job. The AWS 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 AWS 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 aws 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 aws data engineer certification course, you’ll work on real-world datasets and projects to build practical experience. The AWS 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 aws 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 aws 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.

The aws 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 AWS Data Engineering training includes practical exercises and projects that reinforce your understanding, making it more engaging than just pre-recorded content.

Yes, aws 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 AWS Data Engineering certification, which will validate your skills in working with cloud-based data systems and big data technologies.

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