Cloudera Data Engineer Certification Exam 2025

Master Spark, Airflow & Iceberg: Complete CDP Data Engineer Certification Prep

Cloudera Data Engineer Certification Exam 2025
Cloudera Data Engineer Certification Exam 2025

Cloudera Data Engineer Certification Exam 2025 udemy course free download

Master Spark, Airflow & Iceberg: Complete CDP Data Engineer Certification Prep

Cloudera Data Engineer Certification Prep

Elevate your data engineering career with this comprehensive, scenario-driven preparation course designed to help you master the essential skills and pass the certification exam with confidence.

What This Course Covers

  • Spark over Kubernetes & DataFrames: Learn how to deploy and scale Spark jobs on Kubernetes, process massive datasets using DataFrames, and integrate seamlessly with Hive for distributed persistence.

  • Workflow Orchestration with Airflow: Build robust ETL pipelines using DAGs, schedule incremental data extractions, and implement quality checks for reliable, automated workflows.

  • Performance Tuning & Query Optimization: Unlock Spark’s inner workings—optimize joins, use caching effectively, design partitioned and bucketed tables, and leverage explain plans to identify bottlenecks.

  • Deployment Techniques & Apache Iceberg: Utilize Cloudera’s Data Engineering Service via CLI and APIs, manage Iceberg table formats with features like schema evolution and time travel, and prepare for real-world production scenarios.

Who This Course Is For

  • Aspiring and practicing Data Engineers aiming for the Cloudera Data Engineer certification.

  • Data Engineers & ETL specialists looking to build performant, scalable pipelines in Spark and Airflow.

  • Engineers exploring modern data storage with Iceberg and distributed execution on Kubernetes.

  • Anyone wanting practical, hands-on mastery of Cloudera’s platform for job-ready skills.

Why This Course Works

  1. Four laser-focused practice papers that mirror real exam scenarios.

  2. Hands-on exercises and downloadable materials for practical application.

  3. Step-by-step guidance through complex workflows—from implementation to tuning and deployment.

  4. Clear explanations of optimization strategies to help you build efficient, maintainable pipelines.