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 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.