Mastering a field requires deliberate practice.
I will take you on a journey to navigate the journey to data engineering mastery. Let’s Start!
Our journey to mastery consists of two levels, you can think of those levels as the way from junior to senior data engineer.
- Level 2
- Get Familiar With At Least One Cloud Platform
- Work on Real-World Projects
- Implement Data Quality Practices
- Stay Updated with Trends
Level 1 – > Mile Journey start with a step
- Start by understanding the definfion and data engineer resposablities .
Technical skills is a major step that consists of 3 main parts. - Technical skills is a major step that consists of 3 main parts.
- Programming Languages: you should learn at least one of those languages (Python, Java, Scala).
- Data Base Management: Start by learning SQL and basic database concepts like tables columns and records.Then the EDR diagram to understand the relations between tables.
- Data Warehousing: learning data warehouse concepts like modeling. This is preferred to come after making some progress on learning the database.
Understanding ETL (Extract, Transform, and Load) is important, but applying it is more crucial, especially using modern tools like Apache Spark, Flink, and Apache Beam. You could learn anything! - Your network is your networth , by joining data engineering communities on linkedin or any platform and Attending conferences and Meetups .
Full Flow For Level 1
Great job on finishing Level 1 :D Now, let’s gear up for Level 2 — your next adventure awaits! (will be posted soon) Conclusion:
In conclusion, Mastering a field can be accomplished by following a series of organized steps followed by review and refinement. I introduced the first phase (Level 1) for mastering the data engineering field, Stay tuned for the second phase (Level 2), where we’ll dive deeper into their techniques and implications for the future.
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