Data Engineer Job Description

In recent years, data engineers have become highly sought after because of the incredible value they bring to organizations regarding data mining, analysis and implementation. They help create and maintain analytic infrastructures and monitor the functions of almost any data system. They design, develop, test, monitor and maintain databases and large-scale processing data systems. They also create the processes to be used in the:

acquisition
mining
verification of data

With the advent of big data analytics, data engineers continue to hold a key role in any organization. There are currently about 11,000 active data engineers across the world. Most of them work for multi-national corporations that handle large-scale data. Others work as consultants and independent contractors. This post will shed more light on what exactly data engineers do, their annual income, future career outlook and qualifications.

How Much Does a Data Engineer Make?

Based on a report posted by PayScale, data engineers earn an average income of $95,517 per year. The lowest 10% of earners make less than $67,000 while top 10% make over $135,000/year. Their pay largely depends on the level of experience, location and company. While entry level data engineers with less than one year of experience can expect an average base salary of $78,387/year, mid-career professionals can expect a significantly higher average wage around $109,000/year.

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As we mentioned, location also plays a significant role in how much a data engineer can expect to make. Data engineers in San Francisco, California earn a self-reported average of 30.5% more than the national average. Engineers in New York and Seattle also make significantly more than average. Engineers in Chicago make slightly less than average.

What Does a Data Engineer Do?

Data engineers are data science professionals who design, develop and manage the data infrastructure and systems necessary for:

collecting data
transforming raw data
storing data
processing data
distributing data

They design the scripts, codes and techniques used to extract and store such data and create data reports using various tools. Other data engineer responsibilities include:

Ensure all data systems meet industry practices and business requirements.
Research new uses for existing data.
Design, develop and install data recovery procedures.
Recommend ways to improve quality, efficiency and reliability of data.
Work together with data scientists, data analysts and data architects on data project goals and objectives.

What Data Engineer Skills Do I Need?

Data engineers possess certain skills set. They have a deeper understanding of SQL and other database solutions such as Bitable and Cassandra. They have a lot of experience with:

Data warehousing: A data warehouse is a centralized repository that stores, integrates, and manages large volumes of data from different sources within an organization. Data engineers design and build these data warehouses so they need to be familiar with data warehousing concepts and platforms like Google BigQuery and Snowflake to manage large datasets and facilitate efficient data analysis.
ETL tools such as Segment and Stitch Data: Extract, Transform, and Load, or ETL are software applications that help move data from source systems and transform it into a suitable format to be loaded into a data warehouse or database. Data engineers must understand the processes and tools used in ETL.
Big Data Technologies: Data Engineers need to be familiar with big data frameworks like Apache Hadoop and Apache Spark. These technologies help them handle large volumes of data efficiently.
Data Modeling: Data engineers need to understanding data modeling concepts and techniques. These help them design efficient data structures and schemas that support data analysis and reporting.

They are also able to conduct statistical and quantitative data analysis and prepare presentations to management and stakeholders. Knowledge of coding and data machines is also a necessity.

As a data engineer, you’ll also need soft skills. While technical skills are crucial for a data engineer, soft skills are equally important. Some of the most essential soft skills to have include:

Problem-Solving: Data engineers deal with many complex challenges related to data integration and transformation. They must be able to break down problems and analyze the root causes in order to devise an innovative solution.
Communication: Data engineers typically work as part of a team. They often collaborative with other team members, stakeholders and even other departments. They need to explain technical concepts to people who are non-technical while gathering requirements. Data engineers also need to share progress updates in an understandable manner.
Attention to Detail: Precision is crucial in data engineering to ensure accurate data processing and reliable systems. Data engineers should follow a meticulous approach to their work in order to prevent errors that could impact downstream analysis and decision making.
Adaptability: Data engineering is a constantly evolving field with new technologies and techniques emerging regularly. Data engineers should be adaptable and open to learning new tools and approaches to stay current and provide the best solutions to data challenges.

Do I Need a Degree to Become a Data Engineer?

Earning a data engineering degree is the first step toward a career in this exciting field. The degree can be in a variety of areas including:

computer science
information technology
computer engineering
software engineering

These data engineer degree programs feature courses such as:

data structures
computer programming
database management
mathematics
data mining
information security
software design

The coursework also features one final year project and an internship program from a recognized company. All these programs take four years to complete. However, there are some institutions with accelerated programs that can be finished in three years.

You can improve your career prospects and overall marketability by earning a master’s or doctorate degree. A master’s degree can equip you with specialized knowledge with can give you a competitive advantage over other job candidates. Businesses and organizations seek individuals who can architect and implement efficient data pipelines. A master’s degree can boost your resume, making you stand out from other candidates with only a basic understanding of data management.

Investing in a master’s degree in data engineering can also prepare you for leadership roles within your organization. You’ll be able to guide teams and make strategic decisions that have a direct impact on the company’s success. You can also boost your earning potential since a master’s degree can open doors to more lucrative positions!

What are the Pros and Cons of Being a Data Engineer?

There are some advantages and disadvantages of working in data engineering. Working as a big data engineer will open up a lot of job offers and increase contributions towards satisfying the big data needs of the company. The job offers plenty of room for exploration, allowing the data engineer to interact with a wide variety of data coming from different sources and expand their knowledge base. Other advantages include a peaceful work environment, good salary and increased opportunities for career growth.

The disadvantage of being a data engineer is that they may work very hard but fail to get the desired results within a considerable amount of time. Big data tools are still emerging, which might make it difficult to mine, analyze and monitor data properly. The job can also be boring, especially if the data engineer is the type of person who loves to interact with people.

How Do I Get Started as a Data Engineer?

The first step needed to become a data engineer is to look for some work experience immediately after graduating from college. A majority of employers want applicants who have at least three years of experience working with database systems and analytics. Data engineers can work for a startup for a lower salary, be a freelancer or handle their own data engineering projects. They can also work as a volunteer in a big data company or nonprofit institution. In addition to experience, data engineers may need to get proper certifications. They can choose from a variety of certifications including:

IBM Certified Data Engineer
Microsoft Certified Solutions Expert
CCP Data Engineer
Google Certified Professional

All these certifications focus on the application of data engineering skills and ETL tools.

What is the Future Job Outlook for Data Engineers?

Data engineering is a growing profession, with many opportunities for employment and career growth existing across all industries. According to a research study done by IBM, the demand for data engineers and scientists will increase by 28 percent in the next three years. This represents good prospects to those who want to pursue a career in data engineering or science. About 59 percent of the jobs in demand will be in the field of finance, insurance, IT and professional services. The research also found out that the demand for data engineers has surpassed that of data scientists. The main reason for this is that data engineers develop and maintain the infrastructure that keeps data secure and moving smoothly. Hence, companies are increasingly looking for professionals who can help them facilitate a secure and smooth movement of data across all networks.

A data engineer works to design, develop and monitor a company’s data systems. The job is highly specialized, attracts good salaries and provides a great room for improvement. If you are passionate about mathematics and programming and enjoy working with computers, a data engineering job can be a perfect choice for you.

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