Big Data for Beginners: English Tutorial | Data Engineer | A to Z

Roadmap for Big data | Data Engineer :

1. Build a strong foundation in computer science and programming. Data engineers need to be proficient in a variety of programming languages and comfortable with complex technical concepts.

2. Learn about big data and distributed systems. Familiarize yourself with technologies like Hadoop, Spark, and MapReduce, as well as NoSQL databases like MongoDB and Cassandra.

3. Gain experience with data processing and ETL (extract, transform, load). Learn how to extract data from a variety of sources, transform it into a usable format, and load it into a data warehouse or other storage system.

4. Learn about data warehousing and business intelligence. Understand how data is stored and queried in data warehouses, and learn how to use BI tools like Tableau to visualize and analyze data.

5. Build a portfolio of projects. As you learn and gain experience, be sure to document your work and build a portfolio of projects that showcases your skills as a data engineer.

6. Consider earning relevant certifications. While not required, certifications like the Cloudera Certified Data Engineer or the Google Cloud Certified Professional Data Engineer can help you stand out in the job market.

7. Keep learning and staying up-to-date on new technologies and best practices. The field of data engineering is constantly evolving, so it's important to stay current and continue learning throughout your career.