Cloud Computing
Mastering AWS Elastic MapReduce (EMR) for Data Engineers
This course is a comprehensive, hands-on training program designed to teach data engineers, cloud architects, and analytics professionals how to build, manage, and optimize scalable big data processing pipelines using Amazon EMR.
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Included with Skilldacity Membership
About This Course
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This course is a comprehensive, hands-on training program designed to teach data engineers, cloud architects, and analytics professionals how to build, manage, and optimize scalable big data processing pipelines using Amazon EMR. This course provides deep practical experience with Spark, Hadoop, Hive, Presto, and other distributed processing frameworks running on EMR. You’ll learn how to design EMR clusters, optimize performance, integrate with data lakes, automate workflows, and secure your big data environment using AWS-native tools.
Through guided labs and real-world projects, you will gain the knowledge needed to process large datasets, tune EMR clusters for cost and performance, and design production-ready big data pipelines on AWS. Whether you're working with batch analytics, ETL pipelines, machine learning preprocessing, or real-time workloads, this course equips you with the skills required to deliver efficient and reliable data engineering solutions using EMR.
What You’ll Learn
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EMR Foundations
Understanding EMR architecture, components, and the Hadoop ecosystem
Working with Spark, Hive, Presto, and other EMR-supported frameworks
Building and configuring EMR clusters for different data workloads
Data Processing & Pipelines
Running distributed Spark jobs on EMR
Implementing ETL/ELT workflows using EMR and AWS Glue
Integrating EMR with S3 data lakes, Lake Formation, and Athena
Using EMR notebooks for interactive development
Optimization & Cost Efficiency
Autoscaling strategies for EMR clusters
Spot vs. on-demand vs. reserved instances for EMR workloads
Performance tuning for Spark, Hive, and HDFS
Choosing cluster modes (transient vs. long-running)
Security & Governance
Securing EMR with IAM roles, KMS encryption, and Kerberos
Managing data access policies and fine-grained permissions
Private networking, VPC configuration, and secure connectivity
Automation & DevOps Integration
Using EMR Studio and EMR APIs for workflow automation
Integrating EMR with Step Functions, Airflow, and Lambda
Monitoring, logging, and troubleshooting EMR workloads
Real-World Big Data Scenarios
Designing production-grade data pipelines
Handling large-scale batch and streaming workloads
Building scalable machine learning data prep pipelines
Skills You’ll Gain
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Career Path
Cloud Computing
Provider
Vendor Reference
Level
Advanced
Certification
Certification Reference
Access
Included with eligible Skilldacity subscription
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