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What is a Data Engineer ?

In the world of big data, every job works together in order to understand the data collected and make the best use of it for the business. The role of a data engineer is to prepare the infrastructure like algorithms that data scientists and data analysts to analyze in order to enable the business to make the best decisions based on their findings.
Summary

What Is a Data Engineer? — Develop the Skills You Need For Your Career In data engineering

When we think of engineering, we often think about heavy machinery. We think of careers that involve hardhats and jumpsuits, careers that deal with many cogs and gears. But engineering is broader than that. Live Science defines engineering as “the application of science and math to solve problems.” When thought of in those terms, it’s no wonder that the data industry requires data engineers.

In the world of big data, every job works together in order to understand the data collected and make the best use of it for the business. The role of a data engineer is to prepare the infrastructure like algorithms that data scientists and data analysts to analyze in order to enable the business to make the best decisions based on their findings. And with an average of 1.7MB of data created per person per second in 2020, there’s plenty of data for data engineers to work with.

But what exactly goes into a career as a data engineer? What are the skills and university degrees that you need to pursue a career in data engineering? Let’s break that down.

What Do Data Engineers Do?

Data can come from various places, and it often depends on the business. For instance, the small independent bookstore might have a website, a Facebook page, or an app that allows customers to make orders remotely or connect with the store. Every time the customer engages with these elements, they create data which can be collected, analyzed, and used to inform future business choices. Even simply signing up with a username and password can create a cookie, which are used to identify that particular customer. A major corporation undoubtedly has a major online presence, as well as apps from which users create data.

All that data works to tell business executives how their customers prefer to engage with their business and what kind of services they wish to receive from them. It’s almost like a comment card that’s created by customer engagement itself. To interpret this data and to make the most of it requires teams of data professionals.

Data engineers are just one part of the team of big data professionals who work to optimize the data created and collected, but they are an important part. From small independent bookstores to major international corporations, data engineers help business executives to connect with their customer base. The role of a data engineer, in particular, is to develop data algorithms and infrastructures that make the data easier to analyze.

Some of the job duties of data analysts include:

  • Design, develop, and test data pipeline infrastructures and database systems
  • Build and test algorithms and predictive models according to the busines’s requirements
  • Ensure that all current data infrastructures and processes meet industry standards
  • Utilize cutting edge data engineering technologies and software
  • Search for elements of the data collection and analytic processes that need improvement and improve them
  • Collaborate with data analysts, data scientists, and business executives to improve data models
  • Implement systems to monitor data quality for optimized accuracy and clarity
  • Utilize data from a wide variety of sources including SQL, AWS, spark, and hiveSQL

Types of Data Engineering Jobs

There are a number of aspects to data engineering, so it only makes sense that there are a number of different types of data engineering jobs. One data engineer might focus more on the coding and development side of things, while another data engineer might have a more analytical bent. Here are the different types of data engineering jobs you might find:

Data Architect or Builder

Builders are responsible for developing the data pipeline infrastructures that all other data professionals within the business will use. They will save data from various cloud, streaming, app, or social media sources and create the collection processes to gather that data.

Database Administrator

Database administrators are responsible for testing, designing, and maintaining database systems that are used to store data once it’s collected. They not only get the database systems up and running but test them and optimize them for more efficient and secure operation. It’s the database engineers who ensure that data collection and storage all runs smoothly.

Analytical Engineer

An analytical engineer utilizes programming languages like Java, Python, and R and databases like SQL and NoSQL in order to better understand the data and marry data processing systems. Where database administrators ensure that the database runs smoothly, analytical engineers search for ways to optimize the processes in place and the way of working with them.

Data Engineering vs. Data Science: Are Data Engineers a Type of Data Scientist?

Engineering is a science and engineers are a type of scientist, so it’s understandable that data engineers and data scientists can often be confused. In fact, data scientist is often misused as a blanket term that encompasses data engineers, data analysts, and many other careers. However, the role of a data scientist is actually quite different. Think of a data engineer as an architect, creating the systems within which a data scientist works.

Data Scientists

  • Create predictive algorithms to answer questions according to the business’s needs
  • Perform industry and business related research through which to view the data
  • Leverage data against various internal and external sources
  • Utilize machine learning to organize undefined sets of data
  • Clean and organize data provided within the database systems created by data engineers

Data Engineers

  • Create and maintain architectures in which data scientists work
  • Search for opportunities for new and improved data acquisition
  • Design data set processes for data mining and data models
  • Searches for and implements ways to improve data collection and data quality
  • Utilize programming languages to combine data systems for optimized use

Data engineers are the organizers, designing, testing, and maintaining the systems in which data scientists are able to ask the questions needed of the business.

What Systems Does a Data Engineer Use? Tools for Engineering Data Effectively

It’s safe to say a data engineer needs to know their way around multiple data and programming systems in order to do their job well. In some cases, data engineers are the ones creating those systems. In others, they might work within existing systems to collect data and create the data architecture and database systems they need. Regardless, there are a number of tools and processes with which a data engineer should be familiar for their job, including:

  • Programming languages like Java, Python, and R
  • Relational database systems like SQL and document-oriented database systems like NoSQL
  • Cloud migration programs such as AWS, Microsoft Cloud Azure, and Google Cloud
  • Data warehousing like Hive or Apache Spark

And, of course, an engineer should have a creative mind for programming themselves in order to be the “architect” of big data. For that, a data engineer must have the right skills.

Data Engineer Qualifications — What Do You Need?

As with any other career, in order to be a data engineer, there are certain skills that you first have to master. Aspiring data engineers should both have the education and the skills in order to be eligible for a career in their chosen field.

Education Requirements for a Data Engineer

For any engineering career, a knowledge of math and sciences is a must. If you want to get started in a Data Engineering career, you can choose to pursue a Master’s degree, but this is not mandatory. Our Data Science bootcamp is another option you can choose if you want to become a Data Engineer. Combined with an experience in web development, this bootcamp will definitely allow you to succeed in this position.

Technical Skills For a Data Engineer

But what does all that education earn a student at the end of the day? It earns aspiring data engineers valuable skills that they’ll be required to have when they apply for a position. Some of these skills will be required, while others will make candidates much more appealing in a job interview. These data engineering skills include proficiency in:

  • Amazon Web Services (AWS)
  • Apache Hadoop, Hive, Kafka, and Spark
  • Cloud platforms
  • Data architectures, models, and algorithms
  • Java
  • Python
  • Rest APIs
  • SQL and NoSQL

Personality Traits You Need For a Career in Data Engineering

It takes more than just technical skills and education to be a great data engineer. You also need the right kind of personality. A data engineering career can be a demanding one, and it may not be for everyone. However, character traits can be developed in the same way that skills can. If data engineering is your dream career, here are a few personality skills that you’ll want to hone:

  • Multiple disciplines. Many data engineers come from a computer science or data science background, but others are also disciplined in fields such as IT, computer engineering, or statistics. When it comes to data engineering, it helps to be a jack of all trades in the world of data and computer engineering.
  • Problem solving. Data engineers are more than just architects. They are also responsible for testing and maintaining the data architecture that they design, and looking for ways to improve the data processes. All of that requires a mind for problem solving and innovation.
  • Teamwork. Data engineers have to work with each other, as well as working with data scientists, analysts, and business executives. A good data engineer understands that they’re part of a bigger picture and works accordingly.
  • Eager to Learn. Data engineers are required to stay on top of the current industry trends in order to constantly be seeking to improve their business’s methods of data collection and processing. Because of this, it’s important for data engineers to be eager to learn and grow.
  • Flexibility. This is another important trait due to the constant growth of the big data industry. With constant changes to technology and platforms, data engineers should be able to go with the flow.

How Much Money Do Data Engineers Make?

The world of data is constantly growing and all kinds of businesses find themselves in need of the help of a data engineer. Companies like Amazon, Hewlett-Packard, and Facebook all hire data engineers to help optimize their business through the use of data. Because of the increasing demand, a career in data engineering can be quite a lucrative one, often paying well into the 6 figure range.

According to Payscale, in the United States: the average annual salary of a data engineer at Amazon is $110,361. Facebook pays data engineers over $133,000 per year on average. Even gaming companies like Procter & Gamble hire data engineers, with an average salary of $79,000.

Beyond just the financial security of work as a data engineer, there’s also plenty of room for growth within the career. In some cases, data engineers go on to become senior data engineers, mastering their chosen field and passion. Others, however, grow from data engineer to data scientist. A data engineer who loves the building and software element of things might decide to take the next step and become a lead software engineer, a career that can pay as much as $142k each year from companies like Capitol One Financial Corp.

A career as a data engineer is both lucrative and fulfilling, and it could be just the beginning of your career as an engineer or a data professional.

How To Become a Data Engineer: Learn From and Connect With Experts at Le Wagon

Many industries come and go, but the big data industry has only grown since its beginning and continues to grow at an alarming rate. This is the perfect time to pursue a career in data engineering as the demand continues to widen. Are you passionate about math and science? Are you excited about all the potential that can be found working with data, and looking for a career that offers versatility and stimulating challenges? If so, a career in data engineering is the perfect path for you.

Our 9-week Data Science bootcamp, also available in 24-week part-time, teaches major programming languages such as Python, machine learning, and an entire week dedicated to data engineering.

While you take these courses, you can enjoy lectures, challenges, live-coding, and instruction and inspiration from established experts in the field. It’s also a perfect time to network, both with other up-and-coming data professionals as well as more experienced vets in the big data industry. After all, getting involved in the community is just as essential to thriving in your chosen field as having the right skills and education. Le Wagon offers all of the technical tools you need as well as putting you in a position to get the most of the community.

Aspiring Data Engineers, Get Started Today In Pursuing Your Dream Job. Contact Le Wagon!

Want to take a deep dive into the Data Science and web programming skills you need in order to become a data engineer? Le Wagon has got you covered with their intensive coding bootcamps.

Download our syllabus below to discover our Data Science course and learn more about our alumni and community! And for answers to frequently asked questions, head here.

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