What is Data Engineering? The In-Demand Career of 2024

Tabel of the content

• What is data engineering?
• What do data engineers do?
• Why should you consider studying data engineering?
• What are the top skills required to become a good Data engineer?
• Summing up!

Everything from sales performance to stock price and consumer feedback influences business operations. You see, businesses of all sizes generate enormous data annually to comb through to address critical business issues. However, understanding these complex numbers isn’t always intuitive or easy. It is where data engineering comes into the picture.

Data engineering is an emerging field with a glorious scope and career opportunities. It makes a lucrative call to the working professionals who look forward to upscaling their skills and career. Are you also one of them? If so, consider boosting your career trajectory by enrolling in a Data Engineering certification course. Keep reading on as we delve deeper into the details of this domain.

What is data engineering?

Data engineering is a systematic process of extracting, transforming and loading data for further use. To be more precise, data engineers collect raw data from multiple sources and in various formats, convert it into an understandable form and share it with data scientists.

The ultimate goal of this department is to make crucial business data accessible, consistent and reliable for data scientists. They will further churn the data for future applications. This technology empowers managers to identify practical applications of numbers to help their companies thrive effectively.

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What do data engineers do?

What is data engineer? In simple terms, data engineers assemble different pieces of the data ecosystem within a business. They accomplish it by:

• Accessing, gathering, auditing and processing data from various systems and applications into a usable state.
• Developing and maintaining effective databases
• Structuring data pipelines
• Monitoring and managing data systems like security, scalability, etc.
• Implementing the outputs shared by the data scientists in the best scalable way.

However, effectively handling all these functions need one particular skill – Programming. So, the crux is that data engineers are ideally software engineers with expertise in data technologies. Please note that this role differs from what data scientists and analysts perform. While they focus more on data analysis, the data engineers develop pipelines to ensure everyone gets access to the required data.

Why should you consider studying data engineering?

It brings us to the top three reasons you should consider building a career in data engineering. Stay with us as we shed light on them:

Data engineering is the backbone of data science

First of all, you should know what is data engineering. Data engineers are ideally on the front lines of effective data strategy operations. They are among the first to encounter the influx of unstructured and structured data into the business’s systems.

These professionals are the ultimate foundation of data strategy. So, they are like the Lego blocks, without whom businesses can’t build their Lego castle. These professionals act as amplifiers of data strategy outcomes. They are the reliable shoulders on which data scientists and data analysts stand.

Promising scope

As we enter 2024, data engineering is one of the most important and lucrative career options. As per the latest reports, data engineering and global big data services are expected to cross USD 77.37 billion by the end of 2024. This industry will grow at an impressive CAGR of 17.60%. There’s more to it.

According to a survey, a massive 40% jump has been witnessed in the data engineering job openings compared to only 10% in data science profiles. As far as the remuneration part is concerned, data engineering is a well-paying career. As per the data collected by Glassdoor in May 2022, an average data engineer earns around $115176 to $168000 per annum. All these stats speak volumes about the glorious future of this industry.

Also Read, data scientist vs data engineer

Become an asset to the organisation

This profile can help you become an asset to the company. How? Let’s find out in this section:

Greater decision-making - Data engineering will become the key driver of quality and productivity in modern businesses. Data engineers will automate most of the manual processes in the coming years, boosting the effectiveness of data-driven decision-making.

Higher insights - Data engineers offer a foundation for developing insights that help companies make the right choices. This domain is expected to evolve further and provide deeper insights into customer behaviour and business operations.

Better consumer experience - Data engineering can impressively churn out data to help businesses understand their buyers better. This process ultimately leads to improved consumer experiences.

Greater competitive edge - Companies that rely on data engineering for managing and sharing complex data will have a higher competitive edge. It leads to better decision-making, higher productivity and enhanced buyer experiences.

Data-driven organisation – Data engineering can help businesses better collect, analyse and process data. It will give rise to more data-driven organisations and make the role of data engineers more crucial.

Improved data protection – Data engineers are well-versed with all the latest data security tools and encryption technologies. It helps them protect sensitive company information against phishing and cyberattack.

Improved business predictions – Data engineers provide accurate data for predictive modelling processes. It will help organisations identify potential risks and predict upcoming advancements better.

What are the top skills required to become a good Data engineer?

Do you feel motivated to step into the dynamic industry of data engineering? If so, here are the top in-demand skills you must have to become an efficient data engineer.

Database systems – Raw data is the primary asset managed and processed by data engineers. So, having a good understanding of various SQL and NoSQL database systems can help you immensely.

ETL tools – Data engineers work extensively on ETL Tools to maintain the data pipelines. So, make sure you are acquainted with the technicalities of these tools. You can also enhance your knowledge by enrolling in Data Science Training programs. 

Data warehousing – What is a data warehouse? It is a massive digital warehouse that stores data for analysis and querying. A business uses multiple internal and external sources for porting data. You should have a good hold on the nuances of this technology to have a smooth upward movement in this profile.

Machine learning – AI, ML and Big Data, often go hand-in-hand. So, basic knowledge of all these technologies will pave the way for smoother collaborations with data scientists and engineering teams. Consulting experts to understand the technicalities of these domains can help you have a safe entry into this industry.

Data structures and algorithms – Data engineers work exclusively with the data functions and data structures of the organisation. It calls for having an impeccable hold on the basics of data structures and algorithms. This knowledge will help you effectively manage Big Data frameworks and define checkpoints. 

Programming skills – As a data engineer, you must have advanced Python, C#, C++, R and Java programming skills. Experts also recommend going for Data Science Training programs for upscaling these skills. Many reliable and competitive online platforms offer advanced training courses in programming skills.

Communication skills – The Big Data engineers collaborate closely with many different teams. For instance, engineering and design teams, development teams, networking teams, etc. Besides, they also need to communicate with clients and other external parties to share data updates. It makes communication crucial to streamline various verbal and non-verbal communication skills.

Analytical skills – Data engineers often encounter several operational and data-related issues and risks. They also closely work with data analysts to develop and design prediction algorithms and data functions. Effective analytical skills are a must to perform these tasks effectively.

Presentation skills – As a data engineer, you will present various data-driven analyses to internal and external stakeholders. It calls for having brilliant presentation skills to keep the stakeholders and customers hooked to their seats.

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Summing up!

Data engineering is an emerging field that includes the acquisition, transformation, cleaning and modelling of complex data. It is an effective process that will help organisations gain a competitive edge by making more data-driven decisions. Experts believe this domain is constantly evolving and will become more important in 2024 than it is today.

Smart professionals who want to improve their career graphs should stay updated with ever-evolving technologies. StarAgile is a leading platform offering various programs and certification courses for professionals who want to shine in the crowd. Our Data Science Certification Course programs are designed to cater to global industrial requirements and address evolving learning needs. Get in touch with our executives to learn about these programs.