How to become Data Engineer in 2023 | CoderMong

 Becoming a data engineer is a challenging but rewarding career path that requires a combination of technical skills, experience, and education. Here is a general guide on how to become a data engineer in 20,000 words:

Start by developing a solid foundation in mathematics, specifically in the areas of statistics and linear algebra. These are the backbone of many data engineering and data analysis algorithms.

Learn programming languages such as Python, Java, and SQL. These are the most widely used languages in data engineering, and are used in many data engineering frameworks.

Understand the basics of databases, including relational databases and NoSQL databases. Familiarize yourself with SQL and learn how to design and query databases.

Learn the basics of big data technologies like Hadoop, Spark, and Hive. These technologies are used to process and store large amounts of data and are essential for data engineering.

Understand the basics of data warehousing, including dimensional modeling, data marts, and ETL (Extract, Transform, Load) processes. These concepts are crucial for designing and maintaining data pipelines.

Learn cloud computing technologies such as Amazon Web Services (AWS), Google Cloud Platform (GCP), and Microsoft Azure. These technologies are increasingly being used to store and process data, and are important for data engineering.

Get experience with data visualization tools such as Tableau, Power BI, or Looker. These tools are used to present data insights to stakeholders and can help you to understand data better.

Work on your own projects to gain practical experience and understanding. Use online resources such as Kaggle, GitHub, and open-source datasets to find datasets and tutorials to work on.

Get experience in related fields such as data science, machine learning, and software engineering. These areas often overlap with data engineering and can provide valuable additional skills.

Stay updated on the latest developments and trends in data engineering by reading research papers, attending conferences, and participating in online communities.

Consider earning a degree in a related field such as computer science, electrical engineering, or mathematics. Having a formal education will give you a deeper understanding of the theoretical foundations of data engineering, and can also open up more opportunities for career advancement.

Build a portfolio of your work, including projects, publications, and any relevant certifications. This will demonstrate your skills and experience to potential employers and help you to stand out in the competitive field of data engineering.

Network and make connections with other professionals in the field. Join professional organizations, attend networking events, and participate in online forums and communities to meet other data engineers and learn about job opportunities.

Finally, consider earning relevant certifications such as AWS Certified Big Data - Specialty, Google Cloud Data Engineer, or Microsoft Certified: Azure Data Engineer Associate. These certifications can demonstrate your knowledge and skills to potential employers and can help you advance your career.

It's important to note that becoming a data engineer is a continuous learning process and to stay updated with the latest advancements and trends in the field. Also, gaining real-world experience through internships, projects, and industry collaborations, is extremely valuable and can give you a competitive edge when applying for jobs.