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Home   >   Careers   >   Data Engineer

How to Become a Data Engineer

Alex Gurevich – Last updated: December 29, 2024

WRITER

Alex Gurevich is the CEO of FinalStepMarketing, a full-service marketing and business consulting firm.

On This Page
  • Data Engineer Degree
  • Become a Data Engineer
  • Job Overview
  • Career Paths
  • FAQs
  • Resources

This guide is all about how to become a data engineer. It includes information on what kind of degree or education is best suited for getting started as a data engineer and potential career paths and outcomes.

Businesses worldwide are inundated with large amounts of data that must be processed and analyzed to help decision-makers provide solutions in operations, such as marketing, sales, production, distribution, and staffing.

These businesses rely on data engineers to design and maintain systems to manage and optimize this data flow.

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Data engineers are pivotal in today’s data-driven world, expertly designing and maintaining robust data systems that enable efficient data collection, storage, and retrieval, essential for insightful analytics and business intelligence.

Data Engineer Degree

To begin a career as a data engineer, you would typically need to earn at least a bachelor’s degree. Four-year degree programs you might consider include the bachelor of science in data science, bachelor of science in data analytics, or a bachelor of science in computer science. More than 100 US colleges and universities offer degree programs in data science.

Common courses found in a bachelor’s degree program in data science or data analytics are:

  • Big data
  • Data mining
  • Data modeling
  • Applied statistics
  • Data warehousing
  • Business analytics
  • Data visualization
  • Database systems
  • Database management

In these courses, you could learn about real-time analytics, mining software, machine learning applications, business intelligence, database design, data security practices, programming languages, data patterns, data structure, file management, data manipulation, and network modeling.

Some bachelor’s degree programs contain internship opportunities so you can apply concepts studied in the curriculum in real-world situations.

Learn more about tech courses

Some companies might prefer a master’s degree, even for non-managerial positions. A master’s degree would also typically be required for advancement in the field. Master’s degrees you could pursue include master of science in data science, master of science in data analytics, and master of science in analytics.

You could also consider a master of science in information systems with a concentration in database management or a master of business administration (MBA) with a concentration in data analytics. 

At the master’s level, courses tend to focus on more advanced topics in predictive analysis, data trends, decision support, statistical analysis, machine learning theory, data architecture, and forecasting. Graduate internships in data science or data analytics are also available.

Large companies such as GEICO and Gap, Inc. offer internships wherein you will experience hands-on learning opportunities in data retrieval, forecasting, statistical modeling, and systems development.

Other companies such as Amazon, IBM, Capital One, and PayPal have hired MS in data analytics students and graduates for internships and full-time jobs.

Learn more about the best tech internships

Case study examinations and data analytics projects are generally major parts of master’s degree studies in this field, providing greater opportunities for hands-on learning and real-world exposure.

Other practices that support a master’s degree program curriculum in data analytics, data science, or a similar area include conferences, symposia, online and live presentations, and career fairs. Hence, you have the chance to network and interact with professionals, faculty, and peers.

How to Become a Data Engineer

With the need to know about complex programming languages and coding, data transformation processes, technical design, and data processing and manipulation, few “entry-level” data engineer jobs are offered. Mainly, at least a bachelor’s degree is required to enter this field, as formal degree programs essentially cover many of the basics needed to begin in the field.

Bootcamps offer an accelerated way to learn various aspects of data engineering. These provide hands-on, project-focused learning methods for data mining, architecture, programming, warehousing, etc.

These bootcamps effectively boost your knowledge, expand your skills, and brush up on advanced concepts to help demonstrate your abilities to prospective employers.

After completing a bootcamp, you might obtain a position and then pursue your degree while working. Or, showing a hiring manager that you attended a bootcamp could show not only initiative but your interest in and dedication to the field.

Certifications are designed to display your abilities and depth of knowledge in programming, analytics, data systems design, and many other areas. These reinforce your skillset within industry-specific applications and systems. Technological companies and professional associations generally offer certifications.

Google alone, for instance, offers eight certifications in and relating to data engineering, including Cloud Network Engineer, Machine Learning Engineer, Data Engineer, Cloud DevOps Engineer, and Collaboration Engineer. 

Examples of other data engineering certifications follow:

  • Amazon: AWS Certified Data Analytics – Specialty
  • Data Science Council of America: Associate Big Data Engineer (ABDE)
  • Data Science Council of America: Senior Big Data Engineer (SBDE)
  • SAS: Certified Big Data Professional
  • Cloudera: Cloudera Data Platform (CDP) Generalist
  • Microsoft: Azure Data Engineer Associate
  • Databricks: Certified Professional Data Engineer

What Does a Data Engineer Do?

The primary responsibility of a data engineer is to develop and use systems to help companies transform raw data into accessible information that can be analyzed and processed.

This allows those in management positions to make decisions and create solutions. They apply their knowledge of programming and coding to develop databases, servers, processing systems, and data warehouses.

The duties of a data engineer would typically include optimizing data delivery systems, analyzing internal data processes, designing data analytics tools, maintaining data pipeline systems, and creating complex data sets.

According to the IT magazine CIO, the responsibilities of a data engineer would look like this:

  • Develop, construct, test, and maintain architectures
  • Align architecture with business requirements
  • Data acquisition
  • Develop data set processes
  • Use programming language and tools
  • Identify ways to improve data reliability, efficiency, and quality
  • Conduct research for industry and business questions
  • Use large data sets to address business issues
  • Deploy sophisticated analytics programs, machine learning, and statistical methods
  • Prepare data for predictive and prescriptive modeling
  • Find hidden patterns using data
  • Use data to discover tasks that can be automated
  • Deliver updates to stakeholders based on analytics

Data Engineer Career Paths

An actual data engineer job description might look like this, based on an actual posting:

Senior Data Engineer

The data engineer will effectively extract, transform, load, visualize critical data and develop a top-notch data system. This system will guide the investment and development strategies.

This is a crucial role in establishing a data-driven approach within the company, enabling them to understand trends, respond rapidly, and make smart investment decisions.

Responsibilities

  • Partner with leadership, engineers, and data scientists to understand data needs and build systems that deliver high-quality and reliable data
  • Own and maintain the data systems that extract, transform, and load data into internal and external tooling
  • Apply proven expertise and build high-performance scalable data warehouses
  • Design, build and launch efficient & reliable data pipelines to move and transform data (both large and small amounts)
  • Design and develop new systems in partnership with software engineers to enable quick and easy consumption of data

Other Example Career Paths

Skills typically highlighted for data engineers include organizational, analytical, communication, time management, problem-solving, and critical thinking.

After obtaining a degree in data science or a related area, you could choose from a few other career paths in addition to data engineering. You might focus on data infrastructures as a data architect or oversee creation and maintenance as a database administrator. A few other career options to consider are:

  • Data scientist
  • Data manager
  • Big data engineer
  • Machine learning engineer
  • Business intelligence developer

According to Payscale.com, the average annual salary for a data engineer is just over $95,981. Senior data engineers realize a yearly salary of nearly $128,133. New York, Seattle, and San Francisco are among the top cities for data engineer salaries, Payscale further reports.

Skills in specific programming languages and other technologies can impact salary; for example, expertise in the programming language Ruby could lead to a pay increase of up to 33 percent for data engineers.

Knowledge of other programming languages and models such as Oracle, JavaScript, and MapReduce could result in a 22 percent to a 27 percent salary increase.

Frequently Asked Questions

What is a data engineer?

A data engineer is a professional who specializes in preparing ‘big data’ for analytical or operational uses. These experts manage and optimize data pipelines and are skilled in data warehousing solutions.

What educational background is required for data engineering?

Typically, a bachelor’s degree in computer science, engineering, applied mathematics, or a related field is essential. Some roles might prefer a master’s degree or specialized certifications.

Which skills are crucial for a data engineer?

Key skills include expertise in SQL and NoSQL databases, programming languages like Python or Java, and knowledge of ETL (Extract, Transform, Load) tools. Familiarity with cloud services like AWS, Azure, or Google Cloud is also beneficial.

Is a background in it or computer science necessary for data engineering?

While it’s common, it’s not always necessary. Individuals can transition from other fields, but they need to acquire relevant technical skills.

What is the typical career path for a data engineer?

Many start as database administrators or analysts, moving into junior data engineering roles, and progressing to senior data engineer or data architect positions.

What industries employ data engineers?

Industries such as finance, healthcare, retail, technology, and any sector that deals with large amounts of data hire data engineers.

Related Resources

  • How to Become a Data Architect
  • Where and How to Find Entry-Level Data Science Jobs
  • Data Science versus Data Analytics
  • Bachelor’s Degree Programs in Data Science and Data Analytics
  • Find a Degree, Certification, Bootcamp, or Career in Engineering

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Alex Gurevich – Last updated: December 29, 2024

WRITER

Alex Gurevich is the CEO of FinalStepMarketing, a full-service marketing and business consulting firm.

ON THIS PAGE

  • Data Engineer Degree
  • Become a Data Engineer
  • Job Overview
  • Career Paths
  • FAQs
  • Resources

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