What Is a Data Engineer? (With Guide on How To Become One)

By Indeed Editorial Team

Updated 24 November 2022

Published 23 August 2021

The Indeed Editorial Team comprises a diverse and talented team of writers, researchers and subject matter experts equipped with Indeed's data and insights to deliver useful tips to help guide your career journey.

Effective data engineers gather and evaluate raw data to guide and counsel executives and leaders on future organisational goals. It's a fulfilling career path that enables you to exercise a wide range of technical and soft talents to promote innovation and progress.

Competent data engineers are scarce in the present employment market, making it an attractive and lucrative career path to pursue if you've got the right passion and skills for it. In this article, we outline what is a data engineer, how much you can earn as a data engineer and how to become one along with the needed qualifications and skills.

What is a data engineer?

A data engineer is an information technology and a computer science expert in charge of creating algorithms based on patterns derived from raw data sets. Organisations may use these algorithms to make better-informed decisions and achieve more successful outcomes. Data scientists typically specialise in a few areas and receive support from a team of other data analysts and scientists.

As an illustration, a data engineer may build an algorithm that detects specific buying behaviours based on past data to boost future sales. In essence, data engineers provide organisations with a better grasp of complicated raw data by giving trends meaning, linking them with organisational goals and advising corporate executives on key discoveries. Outlined below are some additional duties describing what is a data engineer:

  • Creating, building, testing, monitoring and updating algorithms and architectures

  • Transforming raw data into useful information

  • Harmonising algorithms with organisational needs and objectives

  • Creating data set procedures and optimising data retrieval approaches to gather relevant data

  • Employing various programming tools and languages

  • Looking for ways to increase data accuracy, dependability, efficiency and quality

  • Using large datasets to overcome organisational challenges

  • Implementing advanced analytics programmes, machine learning and statistical approaches

  • Preparing data for prescriptive and predictive modelling

  • Extracting error information

  • Using data to find hidden tasks that can be automated

  • Communicating data trends and providing analytics-based updates to stakeholders

How much does a data engineer earn?

In today's digitalised world, data engineering has simplified work processes across various sectors, making it a popular career choice for a lot of professionals. Companies can hire data engineers to continue the development of data-driven techniques in many organisations. It's also a thriving industry, with firms providing competitive compensation packages to recruit the best talents.

As a data engineer, your pay and benefits heavily vary depending on your experience, education credentials. The remuneration package is also heavily reliant on the organisation's size and industry type. The average annual salary for a data engineer stands at $92,867. The figure is substantially higher than the average income for comparable positions in the country, indicating that competent individuals are in short supply. To boost and maximise your earning potential, try to gain as many job experiences and certifications as you can.

Stepped guide on how to become a data engineer

To succeed in your role as a data engineer, you ought to have confidence in your abilities and performance. Outlined below are some pointers you can consider to become a data engineer:

1. Obtain a bachelor's degree

To qualify for an entry-level job in data engineering, you typically are required to have a bachelor's degree in software engineering, software development, applied maths, statistics, computer science, physics or a closely related subject. When considering what degree to pursue, select one that enables you to cultivate your analytical and problem-solving skills. In your journey of obtaining a bachelor's degree, you can expect to gather practical experience through guidance from your instructors and project-based learning styles. Even if you decide to shift industries, this qualification can equip you with various transferable skills.

2. Develop and refine your technical skills

Examine the available job descriptions to find the most marketable technical talents in today's employment market. You can also engage with mentors who possess extensive industry experience to get guidance on the necessary technical skills to thrive as a data engineer. For instance, SQL is a popular programming language for data engineers since it expands your knowledge of database systems. Python and R are two other important programming languages you can consider refining. Aside from coding languages, other hard skills you need may include:

  • Comprehending database structures

  • Integrating data sources

  • Analysing data

  • Understanding machine learning

  • Identifying data warehousing solutions

  • Being knowledgeable on how to build data mining and data pipelines

  • Working closely with data scientists to build the right solutions

Related: 38 MuleSoft Interview Questions (Plus Sample Answers)

3. Look for an entry-level position

Before you can qualify for a data engineering role, you may be required to demonstrate a comprehensive professional experience. As a result, your initial employment may be in an organisation's information technology department. Beginning from the bottom of the career hierarchy provides you with a fundamental grasp of work procedures. It provides opportunities for you to overcome adversity and think creatively.

Working your way through the corporate ladder into a data engineering role allows you to be more confident in your abilities, which you can demonstrate to the hiring managers. The more remarkable your job experience seems, the more employable you can be as a data engineer. This is simply because recruiters can rely on your established professional track record.

4. Get certified in big data

You can validate your abilities and competence to progress your career in data engineering. Having certifications not only attracts the attention of a hiring manager, but also helps you feel more confident and assured in your abilities. If you want to improve certain abilities, you may discover vendor-specific certifications from various technology corporations and institutions. It's safe to assume that employers across the field recognise these credentials and have previously recruited successful individuals with these qualifications. When deciding on a certification, consult with a mentor and assess your strong and weak areas to decide your needs.

5. Pursue a degree in higher education

As technology grows increasingly prevalent in our daily lives, data tools are rapidly changing. Organisations may, in turn, require more workforce to make sense of vast volumes of data as additional channels for data collection open up. As a result, it's critical to ensure that your abilities as a data engineer remain relevant.

Invest in your personal growth by attending workshops that can help you improve your current abilities. You may also choose to learn at your own speed by enrolling in an online course. If you aspire to advance into a leadership or management role, consider enrolling in a master's degree to broaden your knowledge base and practise strategic thinking. Applicants who exhibit a dedication to further education frequently stand out in the eyes of hiring managers.

What does it take to be a data engineer?

On top of your technical skills, you also are recommended to refine your soft skills to overcome challenges and cooperate with other stakeholders at work. Outlined below are some of the most essential soft skills to excel as a data engineer:

Analytical thinking skills

In your role as a data engineer, you're in charge of building algorithms to target specific business activities based on apparent data trends. To do this effectively, it's important that you exercise excellent analytical abilities to retrieve and collect data and make educated judgements pertaining to an issue. You may discover that as you practice your analytical thinking skills, you'd make fewer mistakes.

Meticulous approach

It's easy to lose concentration or get overwhelmed while working with huge data sets. As a data engineer, you are required to be meticulous in your approach. An attention to detail aids in the detection of errors before they escalate into more significant issues. Considering that your aim is to convey accurate information to the stakeholders, paying great attention to detail protects your reputation as well.

Strong communication

There's often a misconception that data engineers work alone. However, the process of creating an algorithm, from ideation to deployment, necessitates collaboration. In this role, you ought to possess both verbal and nonverbal communication skills to communicate properly with others and meet the respective project objectives.

Problem-solving skills

Data engineering is essentially problem-solving. You are to overcome obstacles to make sense of trends and to discover new possibilities. This requires you to remain positive, manage your stress and work with others to maintain productivity.

Is data engineering hard?

With so many tools and methodologies to select from, data engineering may be a challenging and difficult profession. There are also tight deadlines and pressures associated with the job. In addition, you may be required to bridge a communication gap between your department and non-tech management. This, combined with a lack of meaning and monotony, may all contribute to dissatisfaction. Thus, it's essential that you pursue data engineering only if you're genuinely passionate about the field.

Related: What Does a CIO Do? (Definition and Responsibilities)

Salary figures reflect data listed on Indeed Salaries at time of writing. Salaries may vary depending on the hiring organisation and a candidate's experience, academic background and location.

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