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Cloud Data Engineering on AWS & Azure Certification Course

Design & Build Enterprise Data Platforms Across Multi-Cloud Environments

Learn how to design, build, and manage enterprise-grade data platforms across AWS and Azure. This hands-on certification program equips data engineers with the skills to build scalable pipelines, data lakes, and analytics platforms using leading multi-cloud data engineering tools and services.

Instructor-Led Training

Hands-On Projects

Industry Use Cases

Certification Included

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    Course Overview

    Course Image

    Cloud Data Engineering represents the backbone of modern data platforms, where enterprises rely on AWS and Azure to store, process, and analyze data at massive scale.

    In this course, you will learn how to design data pipelines, data lakes, and warehouses using services such as AWS Glue, S3, Redshift, Azure Data Factory, Databricks, and Synapse Analytics.

    Through practical labs and real-world projects, participants will build cross-cloud data engineering solutions using industry-standard ETL/ELT and orchestration tools.

    By the end of this course, learners will be able to design production-ready, multi-cloud data platforms that support analytics and business intelligence at enterprise scale.

    Course Distinction

    What makes our course unique?

    Unlock Multi-Cloud Data Expertise

    Unlock Multi-Cloud Data Expertise

    Master the concepts behind building and managing data platforms across AWS and Azure, transforming the way businesses handle data.

    Expert-Led Industry Training

    Expert-Led Industry Training

    Learn from cloud data engineering practitioners with real-world experience across multiple cloud platforms.

    Hands-On Learning

    Hands-On Learning

    Build real data pipelines and cloud data platforms through guided labs and capstone projects.

    Practical Enterprise Use Cases

    Practical Enterprise Use Cases

    Learn how cloud data engineering can transform industries like finance, healthcare, retail, and manufacturing.

    Course Content

    • Introduction to cloud data platforms
    • AWS vs Azure data services overview
    • Data lakes, warehouses, and lakehouses
    • Core data engineering concepts

    • AWS S3 and data lake architecture
    • AWS Glue for ETL
    • Amazon Redshift for data warehousing
    • AWS Lambda and Step Functions for orchestration

    • Azure Data Lake Storage
    • Azure Data Factory for orchestration
    • Azure Databricks and Synapse Analytics
    • Azure data governance basics

    • Batch and streaming data pipelines
    • Data transformation strategies
    • Pipeline orchestration and scheduling
    • Error handling and monitoring

    • Dimensional modeling for analytics
    • Partitioning and file formats (Parquet, Delta)
    • Data warehouse vs data lake design
    • Cost-efficient storage strategies

    • Identity and access management
    • Data encryption and compliance
    • Data cataloging and governance
    • Monitoring and auditing pipelines

    • Designing cross-cloud architectures
    • CI/CD for data pipelines
    • Performance and cost optimization
    • Enterprise deployment best practices

    Capstone Project

    Design and build a multi-cloud data engineering solution across AWS and Azure that solves a real-world enterprise data challenge.

    Key Features

    • arrow Instructor-led interactive sessions
    • arrow Real-world case studies
    • arrow Hands-on multi-cloud labs
    • arrow Industry recognized certification
    • arrow Access to AWS & Azure learning resources
    • arrow Capstone project

    Skills Covered

    • AWS Data Engineering (Glue, S3, Redshift)
    • Azure Data Engineering (ADF, Databricks, Synapse)
    • ETL/ELT Pipeline Development
    • Data Lake & Warehouse Design
    • Multi-Cloud Architecture
    • Data Governance & Security
    • Pipeline Orchestration
    • Cloud Cost Optimization

    Advancements

    Cloud data engineering is one of the fastest-growing fields in technology, with organizations investing heavily in multi-cloud data strategies.

    ● Cloud Data Engineer ● Data Platform Engineer ● AWS Data Engineer ● Azure Data Engineer ● Solutions Architect - Data

    Professionals skilled in multi-cloud data engineering on AWS and Azure are among the most sought-after roles globally.

    Business Impact

    FAQ?

    Cloud data engineering involves designing, building, and managing data pipelines and platforms on cloud services like AWS and Azure.

    Basic understanding of SQL and cloud fundamentals is helpful but not mandatory.

    Participants will work with AWS Glue, Redshift, S3, Azure Data Factory, Databricks, and Synapse Analytics.

    Yes, participants will receive an industry-recognized Cloud Data Engineering Certification.

    Customized Corporate Training

    We also provide corporate training programs tailored for organizations looking to build multi-cloud data engineering capabilities.

    Custom curriculum

    Industry-specific use cases

    Flexible training delivery

    Enterprise consulting support

    Who Should Attend

    Data Engineers

    Cloud Engineers

    Data Architects

    ETL Developers

    IT Professionals

    Solutions Architects

    Claude for Test Automation Engineers

    Build the Future with Cloud Data Engineering

    Become a specialist in Multi-Cloud Data Platforms across AWS and Azure.

    Learn from industry experts

    Work on real cloud data projects

    Earn certification

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