2023 Databricks ETL Data Engineer From Beginner to Expert

Are you thinking of getting higher income for a long time with a short training period? Then, you come to the right place. As you know AI and big data are the driving forces behind Industry 4.0. Data engineer is high-paid role. As the shortage of data engineers continues and the demand for skilled data engineer is soaring. Switching to data engineer is one of the best options for your career, which can get higher pay, long-term contracts and less pressure. By joining this course, you will know how the front-line data engineers execute ETL with real open banking project from the scratch, get the ready-to-use, practical and powerful ETL framework and the ISTQB testing strategy.  So, it will be highly possible to pass your job interview because you really have the similar capabilities with data engineers who earn $200, 000+ yearly and be able to resolve complex ETL issues on your own after this course.

If you are already a data engineer, this course will sharpen your ETL skills. This course can free yourself via saving huge amount of computing time and cost during ETL process. More importantly, you will get the capabilities of resolving complex issues in terms of performance, stability and reliability. You will enjoy more free time and leave the hard work to the ETL framework and scripts.

With 6 sections and about 5 hours of high-quality content, you will learn the following topics in depth:

Section #1: Values We Can Bring to You

You will understand what valuable capabilities you can take away after this course and extra free live resources you can keep learning.

Section #2: Azure Databricks and Cosmos DB Setup

You are able to set up Azure Databricks, Cosmos DB and connect them on your own.

Section #3:  ETL Project Initialization

Get real commercial open banking project experience from scratch including grabbing business requirement, Coverting it to technical requirement, designing the solution and implementing it.

Section #4: ETL and Testing Business Goal and Test Strategy

Identify business goals we are going to achieve and adopt right test strategies and plan static testing and shift-left testing approach.

Section #5: Data Extraction and Transformation

Implement data extraction and transformation functionalities and create a smart mechanism to detect if data is modified with lower cost in terms of time and efficiency.

Section #6:  Stable and Speedy Data Ingestion

Resolve complex ETL issues in terms of performance, stability and reliability, etc. as an expert and get the powerful framework and scripts and customize them and apply to your own projects.

Last but not least:

Enjoy this course and don't forget to check out my other courses if you want to learn how to test the project with ISTQB recognized automation testing framework:

2023 Databricks ETL Testing Services Complete Guide