As businesses continue to integrate data science and analytics into their daily workflow, growing volumes of data have increased the need for specialized engineers to build pipelines, manage ETL, and build scalable infrastructures.

In other words, they need data engineers to develop and maintain the tools and frameworks needed by data teams to drive business value.

While data-driven businesses were growing in popularity, data engineering was the fastest-growing job in the field. Now, data engineering has been consolidated as a highly sought-after specialty within the world of data science.

Data Engineering Job Duties

The main task of a data engineer is to build systems that collect, process, and store data, particularly in the form of pipelines.

The process by which data engineers create pipelines is called ETL, or “extract, transform, and load”. Essentially, this involves collecting raw data from multiple sources (e.g., CRM and sales data), organizing it, transforming it into clean information, and delivering it to end users such as data scientists and analysts.

However, the specifics of the role vary by company size and by industry.

Larger companies and industries like finance, tech, and retail tend to have more complex data ecosystems, which require engineers to develop sophisticated data applications and pipelines.

In smaller companies, on the other hand, the role tends to fall closer to that of a full-stack data scientist. In other words, they typically require data engineers to manage the entire data ecosystem and perform analytics.

Some of the key duties of data engineers include:

• Collecting and processing raw data at scale
• Designing and building data applications
• Maintaining data infrastructure, pipelines, and databases
• Aligning data applications to business functions
• Optimizing data pipelines for maximum scalability
• Building the infrastructure for processing data from many different sources

What this course is about

This course introduces the Data Engineering Learning Path, designed to help you ace data engineering interviews by practicing key topics and problems.

We’ll look at the skills expected from a data engineer, some tips for interview preparation, and how to make the most out of the data engineering learning path when preparing for job interviews.