Data Engineering

Data Engineering Course

This may seem like a pretty basic data engineer interview questions, but regardless of your skill level, this may come up during your interview. Your interviewer wants to see what your specific definition of data engineering is, which also makes it clear that you know what the work entails. So, what is it? In a nutshell, it is the act of transforming, cleansing, profiling, and aggregating large data sets. You can also take it a step further and discuss the daily duties of a data engineer, such as ad-hoc data query building and extracting, owning an organization’s data stewardship, and so on.


Advanced Data Engineering Course Content Overview

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An interviewer might ask this question to learn more about your motivation and interest behind choosing data engineering as a career. They want to employ individuals who are passionate about the field. You can start by sharing your story and insights you have gained to highlight what excites you most about being a data engineer.
You need an excellent command of scripting languages and common scripting tools such as SQL, Cassandra, or Bigtable. You will need to know how to build infrastructure and architecture for data generation. You will also need to have experience working ETL and other data warehouse architecture. Hadoop-based analytic knowledge is helpful, and coding knowledge will give you an advantage. Finally, knowledge of various systems such as UNIX and Linux is vital.

If you want to try data engineering, several websites such as Udemy and EdX offer data engineer courses. While you usually cannot get certified via this route, it is a good way to test your skills and learn if you have what it takes to be a certified data engineer.
IBM reports that the job growth rate for data engineers will be 28% over the next three years. This is considerably higher than the national average. Almost 60% of the jobs will be in finance, IT, insurance and professional services.
This data engineer interview question may be more geared toward those on the intermediate level, but in some positions, it may also be considered an entry-level question. You’ll want to answer by stating that databases using Delete SQL statements, Insert, and Update is standard operational databases that focus on speed and efficiency. As a result, analyzing data can be a little more complicated. With a data warehouse, on the other hand, aggregations, calculations, and select statements are the primary focus. These make data warehouses an ideal choice for data analysis.
Data engineers must manage huge swaths of data, so they need to use the right tools and technologies to gather and prepare it all. If you have experience using different tools such as Hadoop, MongoDB, and Kafka, you’ll want to explain which one you used for that particular project.
You can go into detail about the ETL (extract, transform, and load) systems you used to move data from databases into a data warehouse, such as Stitch, Alooma, Xplenty, and Talend. Some tools work better for back-end, so if you can communicate strong decision-making abilities, then you’ll shine as a candidate who’s confident in their skills.
Data modeling is the initial step toward designing the database and analyzing data. You’ll want to explain that you’re capable of showing the relationship between structures, first with the conceptual model, then the logical model, and followed by the physical model.
The four Vs are volume, velocity, variety, and veracity. Chances are, the interviewer will ask you not just what they are, but why they matter. You might explain that big data is about compiling, storing, and exploiting huge amounts of data to be useful for businesses. The four Vs must create a fifth V, which is value.
Interested in this in-demand career? Learn the skills you need to become a data engineer in 15 months or less with the IBM Data Engineering Professional Certificate on Coursera. You’ll be able to use Python and Linux/UNIX shell scripts to extract, transform, and load data, work with big data engines like Hadoop and Spark, and use business intelligence tools to extract insights.

Finally, this video from the University of California San Diego might be helpful for preparing for the technical interview. Although it is focused on software engineering rather than data, mastering the foundations of a technical interview may help you land the job.


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