About a decade ago, as the significance of data-driven decision-making became increasingly evident, companies began to hire data scientists by the dozens—leading to major advancements in many industries. 

However, the importance of data engineers—who ensure efficient data collection, storage, and processing—was often overlooked. Which, hello, how could you? Data engineers literally lay the foundation for data scientists’ work. 

This mismatch in hiring led to a shortage of data engineering talent, hindering data quality and accessibility. As a result, data engineers are now in high demand, with even better compensation and career prospects. In fact, data engineer jobs are expected to grow by 21% from 2018 to 2028, which is considerably faster than the average for all occupations. 

In this guide, you’ll learn about the world of data engineering, the real-world opportunities it presents, and how bootcamps can fast-track your lucrative journey to becoming a data engineer. 

Is data engineering a good career path? 

Because data is the driving force behind many strategic business decisions, companies know they can’t afford not to hire data engineers, making it an in-demand career path with high earning and reward potential. 

Here are just a few of the game-changing ways companies (and therefore data engineers) use data: 

• Use data on customer preferences, market trends, and competitor analysis to guide the development of new products; 
• Utilize pricing data and competitor pricing information to set competitive and profitable pricing strategies for products and services; 
• Identify cost-saving opportunities through data analysis to improve operational efficiency and reduce overhead. 

 

 Looking for more options for high-paying jobs? Read High-Paying Jobs for Veterans without a College Degree 

 

 

Do data engineers make good money? 

Data engineering offers competitive starting salaries, even for entry-level positions. 

According to Zippia, entry level data engineers earn $80,000 annually. This is a reflection of the high demand for data engineers and the value they bring to organizations from the moment they step into the role. 

Beyond the competitive starting salaries, the potential for salary progression is remarkable. Zippa reports that the average data engineer salary is $109,675. Data engineers can look forward to steady and substantial increases in their earnings as they gain experience and hone their technical skills further. 

Data engineering offers various avenues for specialization. Whether you choose to focus on big data tools, cloud computing platforms, or specific industries like healthcare or finance, your expertise can lead to additional earning potential. Companies are often willing to reward specialization with higher paychecks and bonuses. 

 Learn more other fast growing career options in: The Fastest Growing Tech Careers (& Essential Skills) in 2023 

What are the basics of data engineering? 

Data engineers are the backbone of data management within an organization. They take on a multifaceted role that involves several key responsibilities and skills critical to the data structure and the success of data-driven enterprises. 

Responsibilities of data engineers

• Data collection: Data engineers are tasked with collecting data from various sources, including databases, APIs, and external data streams. This information can range from customer interactions to sensor data in industrial settings. 
• Data storage: Once data is collected, it must be stored efficiently and securely. Data engineers design and implement databases and data warehouses to house this information, ensuring its accessibility and reliability. 
• Data processing: Raw data often needs transformation to be useful for analysis. Data engineers create pipelines and workflows to process, clean, and prepare data for downstream tasks. 
• Data integration: In organizations, data is scattered across different departments and systems. Data engineers bring together these siloed data sets and sources, enabling a holistic view of the organization’s information. 
• Data pipeline management: Data engineers design, develop, and maintain data pipelines. These pipelines are the digital highways that allow data to flow smoothly from source to destination, ensuring its availability for analysis and decision-making. 

 

Essential skills for data engineers 

To excel in data engineering, you must possess a set of essential skills that form the foundation of your expertise in data solutions. These skills will empower you to navigate the complexities of data engineering with confidence. 

• Programming proficiency: Basic programming skills are crucial. Data engineers often work with languages like Python or Java to manipulate and transform data, as well as to create automated data workflows.
• Database and SQL mastery: A strong understanding of databases, both SQL and NoSQL, is essential. You’ll use SQL for data querying and manipulation, while knowledge of NoSQL databases like MongoDB or Cassandra is valuable for handling unstructured data.
• Big data tools: In the era of big data, you’ll need to be familiar with tools such as Hadoop and Spark. These tools enable the processing and analysis of large volumes of data, making them indispensable in data engineering.
• ETL (Extract, Transform, Load) processes: ETL is a core concept in data engineering. You’ll need to understand how to extract data from source systems, transform it into the desired format, and load it into data warehouses or databases.
• Data modeling: Data modeling is about structuring data to optimize storage and retrieval. It’s essential for efficient data management, and data engineers must be well-versed in this area.
• Data quality and integrity: Ensuring data quality and integrity is paramount. You’ll develop skills in data validation, cleansing data analysis, and anomaly detection to maintain the accuracy and reliability of data.

 

 Hoping to become a digital nomad? Read: How Learning to Code Can Fund Your Global Adventures 

 

What do data engineers do in the real-world? 

Data engineering isn’t just a theoretical concept; it’s deeply ingrained in the technology and services we use every day.  

Here are some real-world applications where data engineers play an important role: 

Social media 📲 

Data engineers ensure the real-time functionality of your favorite social media platforms. They manage the vast amount of user-generated content, profiles, and interactions, making it accessible to users across the globe. 

E-commerce 🛒 

In the world of online retail, data engineers optimize supply chains by managing data related to inventory, order processing, and customer preferences. This helps retailers streamline operations and provide a seamless shopping experience. 

Healthcare 🏥

Data engineers work behind the scenes to manage electronic health records, medical imaging data, and patient information. Their efforts support healthcare providers in delivering accurate and timely care.

Finance 💸

The financial industry relies on data engineers to maintain databases of financial transactions and market data. This ensures accurate financial reporting, risk assessment, and fraud detection.

Transportation 🚗

In the transportation sector, data engineers play a role in managing real-time data from sensors, GPS devices, and traffic cameras. This data is used to optimize traffic flow, improve navigation systems, and enhance the overall transportation experience.

Entertainment 🎲

Streaming platforms and gaming companies depend on data engineers to further analyze data on user behavior, making personalized recommendations and enhancing user engagement.

 

 

 

Is data engineering hard to get into? 

For high school graduates with a passion for computer science and data engineering, bootcamps offer a direct and effective route into this profession. 

In this section, you’ll learn the reasons why bootcamps are an ideal choice, how they compare to traditional college education, and how to find the right fit. 

The bootcamp solution 

If you’re eager to dive into data engineering right after high school, coding bootcamps are the ideal launchpad. These intensive, fast-paced programs are designed with one clear goal: to equip you with the knowledge and skills needed for success in the industry—and fast. 

Bootcamps are all about hands-on learning. You won’t be drowning in theoretical concepts; instead, you’ll be tackling real-world challenges from day one. The practical experience you gain through bootcamps ensures that you’re job-ready by the time you graduate. You’ll work on projects that mirror what you’ll encounter in your future career, giving you the confidence to excel in the workplace. 

Bootcamps vs. college 

While traditional college education has its merits, bootcamps offer an attractive alternative for those seeking a more direct and cost-effective path to data engineering.  

Here’s how bootcamps stack up against traditional college programs: 

• Cost-effective learning: College comes with a hefty price tag, often including tuition, textbooks, and room and board. In contrast, bootcamps are WAY more budget-friendly, allowing you to acquire the skills you need without accumulating substantial student debt. Additionally, bootcamps often offer financing options and scholarships to further ease the financial burden. 
• Focused curriculum: College programs often include a broad curriculum, including general education requirements that might not be directly related to your field of interest. In contrast, bootcamps offer a laser-focused curriculum tailored to the specific demands of the job market. You’ll dive right into data engineering topics, ensuring you acquire the most relevant skills. 
• Shorter duration: Bootcamps are designed to be shorter in duration compared to traditional college programs. While a college degree can take years to complete, you can emerge from a bootcamp in a matter of months. This means you can find yourself in a data or software engineering role faster, minimizing the time spent transitioning from education to employment. 

Learn more about what sets Promineo Tech bootcamps apart in: Are Promineo Tech Bootcamps a Good Fit for Digital Nomads? 

Finding the right bootcamp 

It’s important to note that not all coding bootcamps are created equal. To ensure you get the best education and value for your investment, consider these factors when searching for the right bootcamp: 

• Reputation: Research the bootcamp’s reputation and track record. Look for reviews and success stories from graduates to gauge the effectiveness of their programs. 
• Comprehensive curriculum: A strong data engineering bootcamp should provide a balanced mix of theory and practical experience. Make sure the curriculum covers all the essential topics you need to excel in the field. 
• Real-world projects: The opportunity to work on real-world projects is invaluable. These projects help you apply your knowledge and build a portfolio, which can be a powerful asset when seeking employment. 
• Experienced instructors: The quality of instructors is critical. Experienced instructors with real-world knowledge bring a wealth of practical insights to the classroom. Look for bootcamps that boast a team of seasoned professionals. 

Pre-requisites for data engineering bootcamps 

The Data Engineering Program offered through Promineo Tech is tailored for students with a technical inclination, aiming to familiarize them with the technologies and methodologies in high demand by hiring companies and utilized by real-world data engineers. 

This program is intensive, encompassing a wide range of technologies such as Python programming, Hadoop, and cloud-based services in Amazon Web Services (AWS). Students will gain exposure to data manipulation techniques, including data wrangling, munging, ingestion, and modeling for analytics. 

Upon program completion, successful students will be well-equipped for entry-level roles as data engineers, Python programmers, or business intelligence developers. 

Here’s what we recommend students have before entering this program: 

• Technical aptitude: Data engineering requires a solid technical foundation. Being comfortable with technology, computer systems, and data-related concepts is crucial. This includes understanding data structures, databases, and data processing technologies.
• Logical thinking skills: Data engineers often need to work through complex data problems and design data pipelines. Logical thinking and problem-solving skills are valuable assets for streamlining data processes and troubleshooting issues.
• Comfort with OS file system concepts: A fundamental understanding of the operating system (OS) file system is necessary. You should be comfortable navigating directories, working with file permissions, and managing data files.
• Experience downloading and installing software: Data engineering often involves working with various software tools and platforms. Experience in downloading, installing, and configuring software is a practical skill that will serve you well in this field.
• Experience working with data connections in excel or other applications: While data engineering typically involves more robust tools, experience with data connections in applications like Excel can help you grasp the concept of data integration and data extraction.
• Experience creating macros and functions: Proficiency in creating macros and functions in Excel or similar applications can be a useful skill for automating data-related tasks and understanding data transformation processes.
• Some exposure to programming (helpful but not required): While not mandatory, having some exposure to programming can be advantageous. Familiarity with programming languages like Python, Java, or SQL can aid in data processing and automation. It’s worth noting that data engineering often involves scripting and coding to optimize data pipelines. 

Conclusion 

The talent gap between data scientists and their mandatory counterpart: data engineers, has created a high demand for data engineers, offering attractive career prospects with highly lucrative salaries and ample opportunity for growth. Data engineering will remain pivotal over the years to come in sectors like finance, health care, retail, manufacturing and more. Getting into data engineering can be straightforward, especially with bootcamps. 

Key Takeaways: 

• There is high demand for new data engineers. 
• The average data engineer salary is $109,675. 
• Data engineers must have these essential technical skills: programming, database and SQL mastery, big data tools, ETL processes, data modeling, and data quality and integrity.
• Data engineers play an important role in these industries: social media, e-commerce, healthcare, finance, transportation, and entertainment.
• Bootcamps offer a fast track into this profession. 

 The Data Engineering program offered by Promineo Tech provides a cost-effective, focused way to enter this career fast.