Data Engineer Learning Path

A Data Engineer designs and builds systems that collect and transform the data used to inform business decisions.

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update Last updated 11 days
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A Data Engineer designs and builds systems that collect and transform the data used to inform business decisions. This learning path guides you through a curated collection of on-demand courses, labs, and skill badges that provide you with real-world, hands-on experience using Google Cloud technologies essential to the Data Engineer role. Once you complete the path, check out the Google Cloud Data Engineer certification to take the next steps in your professional journey.
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01

A Tour of Google Cloud Hands-on Labs

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access_time 45 minutes
show_chart Introductory

In this first hands-on lab you will access the Google Cloud console and use these basic Google Cloud features: Projects, Resources, IAM Users, Roles, Permissions, and APIs.

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02

Preparing for your Professional Data Engineer Journey

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access_time 8 hours
show_chart Advanced

This course helps learners create a study plan for the PDE (Professional Data Engineer) certification exam. Learners explore the breadth and scope of the domains covered in the exam. Learners assess their exam readiness and create their individual study plan.

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03

Google Cloud Big Data and Machine Learning Fundamentals

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access_time 5 hours
show_chart Introductory

This course introduces the Google Cloud big data and machine learning products and services that support the data-to-AI lifecycle. It explores the processes, challenges, and benefits of building a big data pipeline and machine learning models with Vertex AI on...

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04

Modernizing Data Lakes and Data Warehouses with Google Cloud

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access_time 8 hours
show_chart Intermediate

The two key components of any data pipeline are data lakes and warehouses. This course highlights use-cases for each type of storage and dives into the available data lake and warehouse solutions on Google Cloud in technical detail. Also, this...

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05

Building Batch Data Pipelines on Google Cloud

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access_time 14 hours
show_chart Intermediate

Data pipelines typically fall under one of the Extract and Load (EL), Extract, Load and Transform (ELT) or Extract, Transform and Load (ETL) paradigms. This course describes which paradigm should be used and when for batch data. Furthermore, this course...

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06

Building Resilient Streaming Analytics Systems on Google Cloud

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access_time 12 hours 15 minutes
show_chart Intermediate

Processing streaming data is becoming increasingly popular as streaming enables businesses to get real-time metrics on business operations. This course covers how to build streaming data pipelines on Google Cloud. Pub/Sub is described for handling incoming streaming data. The course...

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07

Smart Analytics, Machine Learning, and AI on Google Cloud

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access_time 7 hours
show_chart Intermediate

Incorporating machine learning into data pipelines increases the ability to extract insights from data. This course covers ways machine learning can be included in data pipelines on Google Cloud. For little to no customization, this course covers AutoML. For more...

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08

Serverless Data Processing with Dataflow: Foundations

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access_time 2 hours 15 minutes
show_chart Intermediate

This course is part 1 of a 3-course series on Serverless Data Processing with Dataflow. In this first course, we start with a refresher of what Apache Beam is and its relationship with Dataflow. Next, we talk about the Apache...

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09

Serverless Data Processing with Dataflow: Develop Pipelines

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access_time 28 hours 30 minutes
show_chart Advanced

In this second installment of the Dataflow course series, we are going to be diving deeper on developing pipelines using the Beam SDK. We start with a review of Apache Beam concepts. Next, we discuss processing streaming data using windows,...

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10

Serverless Data Processing with Dataflow: Operations

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access_time 13 hours
show_chart Advanced

In the last installment of the Dataflow course series, we will introduce the components of the Dataflow operational model. We will examine tools and techniques for troubleshooting and optimizing pipeline performance. We will then review testing, deployment, and reliability best...

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11

Perform Foundational Data, ML, and AI Tasks in Google Cloud

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access_time 6 hours 30 minutes
show_chart Introductory

Earn a skill badge by completing the Perform Foundational Data, ML, and AI Tasks course, where you learn the basic features for the following machine learning, AI, and data technologies: Vertex AI, Dataprep by Trifacta, Dataflow, Dataproc, Cloud Natural Language...

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12

Build and Optimize Data Warehouses with BigQuery

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access_time 5 hours 15 minutes
show_chart Introductory

Earn a skill badge by completing the Build and Optimize Data Warehouses with BigQuery course, where you will learn how to transform your data warehouse using BigQuery. A skill badge is an exclusive digital badge issued by Google Cloud in...

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13

Engineer Data in Google Cloud

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access_time 5 hours 30 minutes
show_chart Intermediate

Earn a skill badge by completing the Engineer Data in Google Cloud course, where you will learn how to: Build data pipelines using Cloud Dataprep by Trifacta, Pub/Sub, and Dataflow; Use Cloud Storage, Dataflow, and BigQuery to perform ETL; Build...

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14

Build a Data Mesh with Dataplex

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access_time 5 hours 30 minutes
show_chart Introductory

Earn a skill badge by completing the Build a Data Mesh with Dataplex quest, where you learn how to build a data mesh with Dataplex to facilitate data security, governance, and discovery on Google Cloud. You also complete exercises related...

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