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Career Opportunities

The certified individuals can explore a variety of job opportunities. Some of the positions that they can take up include a Software Engineer, a Cloud Architect, a Data Engineer, a Sales Engineer, a Data Scientist, a Cloud Developer, and a Kubernetes Architect, among others. The salary outlook for these job roles is an average of $128,500 per annum.

Reference: https://cloud.google.com/certification/data-engineer

This course will show you how to manage big data including loading, extracting, cleaning, and validating data. At the end of the training, you can easily create machine learning and statistical models as well as visualizing query results. This program is a bit lengthy but you have to practice well to get the knowledge needed on the actual exam. These are the following modules covered in the course:

• Custom Model building Using SQL in BigQuery ML
• Big Data Analytics with Cloud Al Platform Notebook
• Performing Spark on Cloud Dataproc
• Serverless Messaging Using Cloud Sub/Pub
• Creating a Data Lake
• Introduction to Building Batch Data Pipelines
• Introduction to Data Engineering
• Bigtable Streaming Features and High-Throughput BigQuery
• Introduction to Processing Streaming Data
• Prebuilt ML Models APIs for Unsaturated Data
• Building a Data Warehouse
• Serverless Data Processing with Cloud Dataflow
• Custom Model building Utilizing Cloud AutoML
• Advanced BigQuery Performance and Functionality
• Handling Data Pipelines with Cloud Composer and Cloud Data Fusion
• Production ML Pipelines and use of Kubeflow
• Cloud Dataflow Streaming Features

These modules involve everything the candidate requires for passing the Professional Data Engineer certification exam. Thus, you will not miss anything if you are taking this learning program keenly and apply the required knowledge in an appropriate way. You would end up getting a good score and achieving the Google Professional Data Engineer certification.

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