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AWS Certified Data Engineer Course

AWS Certified Data Engineer Course

Master AWS data engineering: Data Ingestion, Data Storage, ETL, Streaming, Data Governance, Security, and more

Live interactive sessions delivered by AWS-certified engineers and cloud data specialists

Practical experience through hands-on projects and quizzes grounded in real world scenarios

Thorough exam preparation encompassing all official AWS Data Engineer certification objectives

Access to AWS user communities and technical knowledge resources

About AWS Certified Data Engineer Course: Overview

This course offers a comprehensive pathway to mastering the design, management, and optimization of data pipelines and modern architectures on AWS. Learners acquire advanced insight and skills for data ingestion, cloud storage architectures, ETL/ELT processing, streaming, data governance, and security, all mapped to the AWS Certified Data Engineer exam. Interactive labs and scenario-based case studies cement understanding and readiness for certification and data engineering practice on AWS.

What Will You Learn in This AWS Data Engineer Program?

The curriculum consists of essential modules tailored to AWS data engineering principles and current technology standards:

Instructor-Led Interactive Sessions

    • Module 1: AWS Data Ingestion and Streaming : Best practices in streaming, batching, and high-volume ingestion with Kinesis, EventBridge, Data Firehose.
    • Module 2: Designing Data Storage Solutions : Strategies for using AWS storage services including S3, Redshift, Lake Formation, and DynamoDB.
    • Module 3: AWS ETL and Data Processing : Data transformation and pipeline management utilizing AWS Glue, EMR, and Lambda functions.
    • Module 4: Real-Time and Batch Data Pipeline Architecture : Design principles for scalable pipelines supporting both live and scheduled workloads for analytics.
    • Module 5: Data Governance and Security in AWS : Policy creation for IAM, encryption, fine-grained access control, and compliance logging.
    • Module 6: Monitoring, Troubleshooting, and Optimization : Methods for real-time monitoring, error diagnosis, and pipeline tuning using AWS monitoring tools.
    • Module 7: AWS Data Lake and Metadata Management : Implementation of data lakes, set up of metadata catalogs, and lifecycle management with Lake Formation and Glue Crawlers.
    • Module 8: Certification Exam Preparation : Coverage of practice questions, mock exams, and review of exam-specific strategies.

    • Comprehensive utilization of AWS Kinesis, Lambda, and EventBridge for advanced data ingestion
    • Development and management of data lakes and data warehouses with S3 and Redshift
    • Construction of complex ETL pipelines using AWS Glue and EMR
    • Building optimized, resilient workflows for both streaming and batch processing
    • Governance strategies involving IAM configuration, encryption, and audit management
    • Continuous pipeline monitoring, failure analysis, and system fine-tuning
    • Metadata and data lifecycle management through Glue and Lake Formation automation
    • Application of practical knowledge to certification requirements using scenario-based exam preparation

    • The role of AWS data engineer is integral to organizations operating at scale in the cloud. Mastery of AWS platforms ensures efficiency, reliability, and security for mission-critical data pipelines supporting analytics, business intelligence, and AI. Certification in AWS data engineering confirms technical excellence in addressing contemporary cloud architecture, performance, and governance demands.

      What Does an AWS Certified Data Engineer Do?

    • Collaborate with teams to translate analytic and infrastructure requirements into scalable data pipeline solutions
    • Build, maintain, and improve ingestion processes for diverse data inputs, supporting both streaming and batching
    • Design ETL systems using AWS Glue, Lambda, and EMR for reliable data transformation and cleaning
    • Enforce data security by applying appropriate access policies, encryption, and monitoring protocols
    • Monitor workflow performance, resolve inefficiencies, and optimize for cost and throughput
    • Manage data catalogs and lakes, ensuring accuracy and robust governance
    • Communicate design architecture and performance metrics to technical and business stakeholders

    • Roles You Can Pursue with This Certification

      AWS Certified Data Engineer
      Cloud Data Pipeline Developer
      Big Data Engineer (AWS)
      Data Integration Specialist
      Cloud Data Governance Officer
      Data Analytics Engineer

      Core Skills Covered

      Data Ingestion and Streaming | Data Storage Architecture | ETL and Data Processing | Real-Time & Batch Pipeline Design | Data Governance and Security | Pipeline Monitoring & Troubleshooting | Data Cataloging & Metadata Management | Certification Exam Preparation

      AWS Data Engineer Projects

    • Construction and optimization of streaming data pipelines bringing in log and sensor data via Kinesis to S3 and Redshift
    • Development of advanced ETL workflows with AWS Glue transforming, processing, and preparing data for analytics
    • Secure data lake design, employing Lake Formation capabilities and IAM configuration for access control
    • Implementation of real-time analytics dashboards utilizing Lambda and Kinesis Data Analytics
    • Monitoring and proactive management of workflow processes with CloudWatch automation
    • Deployment of comprehensive solutions simulating operational enterprise workloads
    • Delivery of an end-to-end capstone project architecting a scalable, secure AWS data platform

    Career Services

    Participation in communication workshops, technical discussion forums, and ongoing educational activities

    Access to exclusive AWS user groups and forums for knowledge exchange

    Involvement in best practice workshops focused on platform updates and pipeline architecture trends

    AWS Certified Data Engineer Certification

    Certification verifies technical achievement in AWS data engineering by evaluating expertise in data design, ETL systems, workflow automation, and governance.

    Earning this credential signals advanced proficiency in building and optimizing AWS data architectures using industry-leading platform tools and services.

FAQ

Key focus is placed on AWS Kinesis, Glue, Redshift, Lake Formation, Lambda, and supporting services for streaming, ETL, storage, and security.

Data engineers, cloud architects, and analytics professionals seeking advanced, production-level skills in AWS data pipeline development and management.

Familiarity with AWS is beneficial but not essential; the training begins with foundational content and extends to advanced, hands-on projects.

The curriculum delivers a balance of live sessions, self-paced modules, interactive labs, and collaborative exchanges, ensuring flexible yet structured progression.

The credential highlights deep understanding of AWS data engineering, reflecting technical capability in building, securing, and maintaining modern cloud data platforms.
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