عراب ال IT 
امتحانات دوليه
Professional Data Engineer
About the Certification
This is an advanced professional-level certification from Google Cloud, within the Data & Analytics specialization. The certification focuses on designing, building, managing, and securing data platforms on Google Cloud using services such as BigQuery, Dataflow, Dataproc, Pub/Sub, Cloud Storage, Cloud Composer (Airflow), Data Catalog, Looker, and more. It covers the entire data journey:
Data ingestion → storage → processing → analysis → governance & security → performance and cost optimization. This certification is designed for Google Cloud data experts and validates your ability to build advanced, scalable Data Analytics and Data Engineering systems that are production-ready and used in large enterprise environments.
Main Curriculum
The curriculum is divided into six main sections
- Cloud Network Design and Planning
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- Designing VPC networks on Google Cloud
- IP address planning and subnet design
- Using Shared VPC
- Network architecture best practices
- Data Quality, Reliability, and Governance
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- Ensuring data quality
- Data validation and monitoring
- Data governance and policy management
- Metadata management and compliance
- Data Analysis and Machine Learning Enablement
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- Enabling advanced analytics
- Supporting Data Science and Machine Learning teams
- Preparing data for ML models
- Integrating with analytics and AI tools
- Data Storage and Data Modeling
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- Selecting appropriate storage systems
- Data modeling for analytics and performance optimization
- Structured and unstructured data
- Managing the data lifecycle
- Building and Operating Data Pipelines
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- Designing reliable data pipelines
- Processing data using batch and streaming models
- Orchestration and workflow management
- Running data pipelines in production environments
- Security, Privacy, and Compliance
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- Securing data at rest and in transit
- Identity and Access Management (IAM) and access control
- Data privacy protection
- Regulatory compliance and standards
Exam Details
- Duration: 120 minutes
- Number of questions: 50–60
- Question types: Multiple-choice and multiple-select
- Language: English
- Passing score: Approximately 70–75% (Pass / Fail)
- Exam fee: USD 200 (taxes may apply in some countries)
- Certification validity: 2 years
Do I need certifications before it ?
No, not at all.
However, it is recommended to have: A strong understanding of Google Cloud fundamentals. Very strong SQL skills, especially for analytics workloads. Hands-on experience building data pipelines or ETL/ELT systems. A solid background in Data Engineering is a major advantage, even without formal certification. Holding the Associate Cloud Engineer (ACE) certification or equivalent hands-on experience can help, but it is not mandatory.
Which certifications are recommended after this one ?
Not mandatory. However, for professionals seeking a strong path in Data Engineering on Google Cloud especially in designing and building pipelines, processing large-scale data, and transforming data into actionable insights the Professional Data Engineer certification is the most powerful specialization.
What are the main career uses of the Professional Data Engineer certification ?
- Data Architecture / Analytics Architect for designing scalable, governed enterprise data platforms.
- Advanced Data Engineering (Streaming / Lakehouse) for real-time processing and modern data architectures.
- Machine Learning Engineering to enable ML and AI workloads.
- Generative AI (Data for LLMs / RAG) to power GenAI solutions with enterprise data.
- Professional Cloud Architect to connect data engineering with cloud architecture.
- Data Governance & Security focusing on quality, privacy, and compliance.
Your Step Toward Data Engineering Mastery :
Passing the Professional Data Engineer exam proves your ability to design and build large-scale data systems on Google Cloud, create robust batch and streaming pipelines, analyze data efficiently using BigQuery, and manage governance, security, performance, and cost optimization in production environments. It is a very strong step for anyone aiming to become a professional Cloud Data Engineer and lead enterprise data platforms in data-driven organizations.
Who is this certification suitable for ?
- Data Engineers, Data Architects, and Analytics Engineers.
- Professionals building ETL/ELT pipelines or big data processing systems.
- Engineers working with Data Warehouses and Data Lakes on Google Cloud.
- Specialists in data analysis, performance optimization, or data governance.
- Roles such as Data Engineer, BI Engineer, Analytics Platform Engineer, Cloud Data Architect, or ML Data Engineer.