What Does A Data Engineer Do? | The Ultimate Guide

Welcome to the world of information technology, where technology is always evolving and data management is more important than ever. For students who are about to graduate, they may be interested in joining a career in data engineering, but what does this professional do?

In this article, we will discuss the role of data science in information technology and what data engineers do daily. We'll also discuss some frequently asked questions about this role.

What Is a Data Engineer?

A data engineer or database engineer is a professional responsible for designing, building, and maintaining the infrastructure and systems needed for handling data. Data refers to any information pulled from customers or interface users that may be used by the company in the future. For example, payment details and contact information may be stored by a company that processes payments through its website.

Their primary goal is to ensure that data is accessible, reliable, and efficiently utilized for analysis and decision-making. Most importantly, the data engineer must ensure that information is appropriately stored and protected and follows the regulatory measures of the government.

Skills Required of a Data Engineer

A data engineer must have the proper skills to develop safeguarded technology to collect, store, process, and analyze large sets of data. They must excel in implementing data quality checks, data validation, and data governance practices to ensure data integrity and compliance.

Since data engineers work primarily in cloud platforms, they should have a solid foundation in AWS, Google Cloud Platform, and Microsoft Azure for deploying and managing data infrastructure.

What Are the Responsibilities of a Data Engineer?

Aside from being employed in big data and the responsibilities related to this professional field, data engineers should equip themselves with the knowledge of what technical skills to expect in this career. Data engineering skills require a heavy volume of technical skills, including:

• knowledge of programming languages
• data processing
• appropriate data storage

Designing Software Systems

Software engineering plays a major role in data because the professional may have to develop internal software from scratch. The most common coding languages used to develop software include:

• Python
• Java
• CSS

Developing Data Set Processes

As a data architect, this professional handles large amounts of data and must comply with governmental entities to ensure proper database management. Large datasets should be easily available to extract, transform, and load across a variety of uses, including data analysis and automation.

Analyzing Data

Within a data warehouse is an immense amount of information that's useful to the company. Likewise, that company may sell consumer data to its partners. Data analytics is an integral part of business intelligence and helps companies understand their consumer better. They may start to identify trends to create a more seamless user experience.

Data engineers should be able to pull data-related information from the system and interpret it for other members of the company.

Coding

As mentioned above, coding is an essential part of data solutions. Data engineers should create data systems with efficient functionality and follow the fundamentals of responsible data storage.

Streamline Data Pipelines Using Artificial Intelligence

Data architectures require the familiarity of orchestration tools like Apache Airflow, Luigi, and Prefect for scheduling and managing data workflows. This allows the data engineer to build relational databases that analyze company information in real-time. Understanding of DevOps practices for continuous integration and deployment (CI/CD) of data pipelines and infrastructure.

Artificial intelligence is beginning to play a larger role in cloud computing as it can provide useful visualization tools for millions of data elements in a matter of seconds.

Communication and Problem-Solving

Aside from the many technical skill sets required in a data engineering job, the professional must be able to collaborate with inter-company teams, including:

• stakeholders
• data analysts
• machine learning teams

How To Become a Data Engineer

To get started as a big data engineer, professionals have to follow a certain number of steps.

Get a Relevant Bachelor's Degree

Starting with a relevant bachelor's degree is essential because it will teach you the knowledge necessary to effectively create data models. Most students opt for a bachelor of science in computer science or information technology.

Gain Experience Through an Internship

Internships are a great way to build skills in data warehousing as well as coding frameworks to build programs before graduating. Look for internships that will align with your career path including junior-level data engineering or data analytics. You may work in programs such as:

• IBM
• Kafka
• Apache Spark

Make sure to list all of your experiences on your resume to showcase what data tools you acquired in your internship.

Earn a Certification

There are a few different types of certifications available depending on the different data engineering roles. Although Hortonworks Certified Data Engineer (HDPCD) has merged with Cloudera, this certification is still valuable for demonstrating skills in Hadoop ecosystem technologies like Hive, Pig, and Spark.

Cloudera Certified Professional Data Engineer (CCP Data Engineer) focuses on building and managing data pipelines using Cloudera's platform. It covers data ingestion, transformation, storage, and analysis. Certified Data Management Professional (CDMP) is offered by DAMA International and validates knowledge in data management and data governance. It is suitable for data engineers focusing on data architecture and data quality.

Determine Whether an Advanced Degree Is Right for You

If you wish to start earning an advanced degree in data engineering, several different degree options can improve your employability. A master's degree in computer engineering can help you build appropriate coding formats and algorithms to optimize scalability. A master's in database management will help teach the necessary information for relational databases, like (SQL) and NoSQL databases.

FAQs About Data Engineers

Ready to get started in data engineering? Here are some frequently asked questions about the profession.

How Long Does It Take To Become a Data Engineer?

In most cases, it only requires four years of a bachelor's degree to get started in a data engineering position. While you may only receive an average salary this can be boosted by additional certifications and advanced degrees later on.

What Is a Typical Day Like for a Data Engineer?

A typical day may include reviewing projects to ensure timely processing of information. The data engineer may check the status of overnight data jobs and ensure all ETL tools (Extract, Transform, Load) run smoothly. They may also troubleshoot and fix any issues that occur in data pipelines. This may involve:

• debugging scripts
• checking logs
• validating data integrity

Can You Become a Data Engineer Completely Online?

Yes, various digital college campuses throughout the United States offer undergraduate and graduate degrees online.

What Is the Difference Between a Data Engineer and a Data Scientist?

While data engineers and data scientists play critical roles in the data ecosystem, they focus on different aspects of the data lifecycle. Data engineers build and maintain systems that allow data to be collected, stored, and processed efficiently. Data scientists analyze this data to extract insights and develop predictive models. Both roles are essential for turning raw data into valuable business insights.

Is Data Engineering a Coding Job?

Yes, some elements of coding do apply to data engineering, though it depends on how high the level of a position. Entry-level data engineering may involve a higher volume of Java and Python coding as they build data sets and learn how to automate functions.