How to Become a Data Engineer in 2023:  5 Steps for Career Success

Written by Varghese George

Mr. Varghese is the Senior Manager for Technology Services Division providing the best of Back-up and Security Solutions to our clients.

Choosing a career as a data engineer is more than a mere professional decision—it's a strategic maneuver toward future-proof success. As businesses increasingly pivot toward data-driven strategies, the role of a data engineer becomes essential and pivotal in shaping the foundations upon which modern enterprises thrive. 

Suppose you want to embark on a fulfilling journey as a data engineer in 2023. In that case, KUWAITNET  is here to guide you through five user-centric steps that guarantee job security and career success.

What is Data Engineering?

Fundamentally, data engineering is the skill of designing large-scale data handling, storage, and analysis systems. This entails building pipelines that can gather raw data from many sources, convert it into a format that can be used, and extract insightful information. Understanding a company's operations—including outreach tactics, sales data, and customer interactions—requires these insights.

Gartner's alarming forecast of an 85% failure rate for data-driven initiatives in 2021 placed a pall over the sector. Despite this dire prediction, businesses are investing more in strong data infrastructures. The need for specialists who can effectively manage the complex world of data has arisen due to this change.

5 Steps to Become a Data Engineer in 2023

According to a 2021 report by DICE, the role of a data engineer experienced a staggering 50% annual growth in 2022. This trajectory underlines the importance of becoming a data engineer in the ever-evolving tech ecosystem.

Step 1: Forge a Robust Programming Foundation

Building a resilient foundation in programming is the first step towards becoming a proficient data engineer. KUWAITNET  recommends immersing yourself in Python, a language renowned for its versatility and wide adoption in the data engineering domain. The simplicity and extensive library support make Python ideal for aspiring data engineers.

Key Areas to Master:

  • Operators, Variables, and Data Types

  • Conditional Statements & Looping Constructs

  • Data Structures (Lists, Dictionaries, Tuples, Sets) and String Methods

Pay special attention to the Pandas library for data manipulation, focusing on real-world scenarios such as data cleaning, extraction, and manipulation.

Step 2: Mastering the Art of SQL and NoSQL Databases

Given its indisputable demand, getting a solid knowledge of SQL is imperative. Concurrently, familiarize yourself with NoSQL. Understanding organized and unstructured data is essential, given the diversity of the data world. Start by learning about Window functions, constraints, joins, and subqueries in basic querying.

Explore NoSQL databases, paying special attention to MongoDB. KUWAITNET  invites you to become familiar with CRUD operations, collaborate with many operators, and comprehend ideas like replication and sharding.

Step 3: ETL Pipelines and Data Integration

In contemporary data engineering, data integration—combining data from several sources—is essential. Pipelines for extracting, transforming, and loading (ETL) are essential. Learn to use important ETL technologies, including Talend, Apache NiFi, and Apache Kafka. KUWAITNET  strongly emphasizes learning best practices and data integration strategies to guarantee accurate data processing.

Step 4: Embrace the Era of Big Data Technologies

Big Data technologies are at the forefront of the dynamic landscape of data engineering. Stay ahead by acquiring knowledge in key technologies:

  • Apache Hadoop

  • Apache Spark

  • Apache Kafka

  • Apache Airflow

  • MongoDB

KUWAITNET advises gaining a foundational understanding of these tools to meet today's industry's intricate data processing demands.

Step 5: Unleash the Power of Cloud Computing

Cloud computing is essential to data engineering because it provides scalable infrastructure and a range of tools for data processing and analysis. Examine Microsoft Azure, Google Cloud Platform (GCP), and Amazon Web Services (AWS). Kuwaitnet suggests learning about Continuous Integration/Continuous Deployment (CI/CD) pipelines and DevOps principles for an extra edge.

Bonus Step: Cultivate Your Communication Skills

Being a successful data engineer requires more than just technical skills—effective communication is essential. Proficiency in collaborating among several departments and effectively communicating intricate technical ideas to a wide range of audiences is essential. Since data engineers frequently have to produce dashboards, reports, and visualizations, they must be adept communicators to share their findings with stakeholders.


KUWAITNET awaits the next generation of data engineers, and with these steps, you are well on your way to becoming a valuable contributor to the data-driven future. Glassdoor reports that the average data engineer in the U.S. earns over $110,000 per year, with seasoned professionals in giant tech companies reaching up to $150,000 per year.

Becoming a data engineer in 2023 involves a strategic blend of technical proficiency, adaptability, and effective communication. By following these five user-centric steps, you position yourself not just for job security but as a trailblazer in a field that promises innovation and growth. Remember, the entire process is as rewarding as the destination, and KUWAITNET  is committed to guiding you every step of the way.