Azure Data Engineer Certification DP-203 Notch up your data engineering career with Microsoft certified Azure Data Engineer Certification course (DP-203). Prepzee brings you a critically curated course by the experts in the industry in Azure DP certification to help you master the skill set required to become an Azure data engineer.
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Aman Yadav
Senior Associate Product at Amazon
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Nice experience, I will recommend it to all the learners who are willing to join and learn IT skills. I was able to switch my domain from non-IT to IT in a reputed MNC
Vishal Purohit
Product Manger at Icertis
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Great learning experience through the platform. The curriculum is updated and covers all the topics. The trainers are experts in their respective fields and follow more of a practical approach.
You are a fresher interested in learning cloud computing, with a specific goal of achieving the Azure Data Engineer Certification.
You do not have coding experience but are looking to start a career in IT by enrolling in an Azure Data Engineer course.
You are familiar with data processing languages like Python, SQL, or Scala and and plan to pursue the Azure Data Engineer Certification to advance your career.
You understand patterns of data architecture and parallel processing, making the Azure Data Engineer Certification a suitable next step.
36 Hrs Instructor-Led Training
32 Hours Hands on & Exercises
5+ Projects and case studies
Microsoft Certified Instructors
Attend as Many Batches for Lifetime
Flexible Schedule
Resume Builder
Mentor Support
An Azure data engineer has expertise in the integration, transformation, and consolidation of data. Azure Data Engineer training helps professionals develop these skills and prepare for the Microsoft Azure Data Engineer certification
In this Azure Data Factory training course, you understand the basics of cloud computing and get introduced to Microsoft Azure. Get knowledge of Azure Synapse Analytics and Azure DataBricks and work with Azure Stream Analysis. Learn how to use data lake and data factory and deploy the same in relevant pipelines.
Equip yourself with the knowledge of designing multidimensional schema for optimizing analytical workloads. Learn how to transform at scale using Azure Data Factory. Also, learn about designing a modern Data Warehouse and securing data warehouse using Azure Synapse Analytics.
Get a thorough understanding of big data engineering. Use Azure Synapse Analytics Apache Spark, loading data with Apache Spark notebooks and transforming data using DataFrames in Apache Spark Pools. All these practical skills are covered extensively in the Azure Data Engineer course to ensure you gain hands-on expertise for real-world applications.
The curriculum of the MS Azure DP-203 Certification course, designed by experts in the industry, is in accordance with the requirements for clearing the Microsoft Azure Data Engineer Certification (DP-203). Other than general guidelines, you will have help with preparing a resume, potential interview questions, mock interviews, and a reliable certification to go with it.
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1.1: Introduction to cloud computing
1.2: What is Microsoft Azure
1.3: Introduction to Azure Synapse Analytics
1.4: Describe Azure Databricks
1.5: Introduction to Azure Data Lake storage
1.6: Describe Delta Lake architecture
1.7: Work with data streams by using Azure Stream Analytics
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2.1: Design a multidimensional schema to optimize analytical
workloads
2.2: Code-free transformation at scale with Azure Data Factory
2.3: Populate slowly changing dimensions in Azure Synapse Analytics pipelines
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3.1: Design a Modern Data Warehouse using Azure Synapse
Analytics
3.2: Secure a data warehouse in Azure Synapse Analytics
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4.1: Explore Azure Synapse serverless SQL pools capabilities
4.2: Query data in the lake using Azure Synapse serverless
SQL pools
4.3: Create metadata objects in Azure Synapse serverless
SQL pools
4.4: Secure data and manage users in Azure Synapse
serverless SQL pools
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5.1: Understand big data engineering with Apache Spark in Azure
Synapse Analytics
5.2: Ingest data with Apache Spark notebooks in Azure Synapse
Analytics
5.3: Transform data with DataFrames in Apache Spark Pools in
Azure Synapse Analytics
5.4: Integrate SQL and Apache Spark pools in Azure Synapse
Analytics
Hands On:
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6.1: Describe Azure Databricks
6.2: Read and write data in Azure Databricks
6.3: Work with DataFrames in Azure Databricks
6.4: Work with DataFrames advanced methods in Azure
Databricks
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7.1: Use data loading best practices in Azure Synapse Analytics
7.2: Petabyte-scale ingestion with Azure Data Factory or Azure
Synapse Pipelines
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8.1: Data integration with Azure Data Factory or Azure Synapse
Pipelines
8.2: Code-free transformation at scale with Azure Data Factory or
Azure Synapse Pipelines
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9.1: Orchestrate data movement and transformation in Azure
Data Factory or Azure Synapse Pipelines
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10.1: Optimize data warehouse query performance in Azure Synapse
Analytics
10.2: Understand data warehouse developer features of Azure
Synapse Analytics
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11.1: Analyze and optimize data warehouse storage in Azure
Synapse Analytics
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12.1: Design hybrid transactional and analytical processing
using Azure Synapse Analytics
12.2: Configure Azure Synapse Link with Azure Cosmos DB
12.3: Query Azure Cosmos DB with Apache Spark for Azure
Synapse Analytics
12.4: Query Azure Cosmos DB with SQL serverless for Azure
Synapse Analytics
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13.1: Secure a data warehouse in Azure Synapse Analytics
13.2: Configure and manage secrets in Azure Key Vault
13.3: Implement compliance controls for sensitive data
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14.1: Enable reliable messaging for Big Data applications using
Azure Event Hubs
14.2: Work with data streams by using Azure Stream Analytics
14.3: Ingest data streams with Azure Stream Analytics
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15.1: Process streaming data with Azure Databricks structured
streaming
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16.1: Create reports with Power BI using its integration with Azure
Synapse Analytics
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17.1: Use the integrated machine learning process in Azure Synapse
Analytics
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Our tutors are real business practitioners who hand-picked and created assignments and projects for you that you will encounter in real work.
Perform standard DataFrame methods to explore and transform data. Key Points: Create a lab environment. Azure Databricks cluster.
The project includes loading data into Synapse dedicated SQL pools with PolyBase and COPY using T-SQL. Use workload management and Copy activity in an Azure Synapse pipeline for petabyte-scale data ingestion.
The project revolves around building data integration pipelines to ingest from multiple data sources, transforming data using mapping data flows and notebooks, and performing data movement into one or more data sinks.
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.
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.
The program helped me strengthen my expertise in modern Azure 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.
I have completed the Data Engineering program with Prepzee, where I learned Azure, 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.
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.
18/04/2026 - 08/02/2026
7:30 pm TO 10:30 pm IST (GMT +5:30)
Online 
12 Hours left at this price!
4.9 Average Rating 14+ Years of experience
Microsoft, Adobe & AWS certified young and dynamic professional with 14+ years of industry experience. Trained 8200+ professionals, and counting, on all cloud technologies including AWS, Azure and GCP, DevOps, AEM, iOS, UI/UX, Digital Marketing & advanced Front End and Backend development technologies.
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4.8 Average Rating 15+ Years of experience
As a Data Engineer, I have 15+ yrs experience working on different cloud environments on various projects.I currently lead multi-work stream projects as a Cloud analyst and DevOps Engineer. Technologies I work on AWS, AZURE,Git hub, Jenkins, Ansible, Docker, Kubernetes ,Python ,Data Science On Azure and many more.
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4.7 Average Rating 12+ Years of experience
Engaging, understanding, and knowledgeable technical trainer with over 12+ years of experience in a variety of software programs and technologies including Data Science, Databricks, Data Lake, Synapse Analytics, Data Factory, Power BI, Business Intelligence AWS, Azure and GCP.
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4.8 Average Rating 17+ Years of experience
Always learning and always yearning with experience of more than 17+ yrs, have delivered more than 200+ mentoring/ training sessions online on Microsoft Azure, Amazon web services, Cyber Security, Python, Tableau and Power BI to more than 20000 students.
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Prepzee's certified alumni work at Fortune 500 companies.
Monitoring and optimizing data storage and data processing
Create and manage data pipeline
