Summary of $100k+ Data Engineer Complete Roadmap 2024 🚀 Skills, Tools, Future Scope, Salary ✅

Summary of the Video: $100k+ Data Engineer Complete Roadmap 2024

In this video, Sahil Gana, a data engineer at a top Canadian bank, shares insights on how to start a career in data engineering, emphasizing the importance of understanding fundamentals and developing a problem-solving mindset. He outlines the essential skills, tools, and methodologies needed to succeed in this field.

Main Ideas and Concepts:

• Mindset for Data Engineering:
  • Emphasizes a problem-solving mindset, crucial for tackling daily challenges in data engineering.
  • Encourages continuous learning and adaptability in a rapidly changing environment.
• Distinction Between Data Roles:
  • Clarifies the differences between Data Engineers, Data Scientists, and Data Analysts.
• Essential Skills and Tools:
  • Basics of Computer Science: Fundamental knowledge required for data engineering.
  • Specific Data Engineering Skills: Tools and technologies specific to the field.
• Key Technologies and Languages:
  • SQL: Understanding and writing efficient SQL queries is foundational.
  • Programming Languages:
    • Python: Recommended for beginners; focus on basic data structures.
    • Other languages: Java and Scala are also relevant.
  • Cloud Computing: Familiarity with virtual machines and cloud services.
• Fundamentals of Data Engineering:
  • Data Warehousing: Understanding the difference between databases and data warehouses, and concepts like ETL (Extract, Transform, Load) and ER modeling.
  • Big Data Ecosystem: Awareness of technologies like Hadoop and its components (e.g., MapReduce, HDFS).
  • Data Processing Frameworks: Learning Apache Spark for in-memory data processing.
  • Real-time Data Handling: Familiarity with pub/sub systems for streaming data.
  • Data Orchestration Tools: Understanding tools like Apache Airflow for job scheduling and monitoring.
• Project Development:
  • Importance of building end-to-end data pipelines using the learned tools and technologies.
  • Suggests utilizing resources like Darshal Parmar’s videos for project ideas.
• Career Transition:
  • Emphasizes that strong foundational knowledge and practical project experience are key to successfully transitioning into a data engineering role.

Methodology/Instructions:

• Step-by-step Learning Path:
  • Start with SQL to understand data structures.
  • Learn a programming language (preferably Python).
  • Familiarize yourself with data warehousing concepts.
  • Explore the Big Data ecosystem and its technologies.
  • Gain proficiency in data processing frameworks like Spark.
  • Understand real-time data handling and orchestration tools.
  • Build projects that incorporate these skills to demonstrate competence.

Speakers/Sources Featured:

• Sahil Gana: Data engineer and presenter of the video.
• Tech TF: Recommended resource for learning SQL.
• Darshal Parmar: Suggested for project ideas and end-to-end pipeline projects.

Notable Quotes

— 00:11 — « Data is the new gold in the 21st century and every candidate needs the path of this data mind. »

— 01:20 — « If you have this mindset, then you are ready to hustle. »

— 01:54 — « It can take a lot of sleepless nights but it is a really rewarding and a fun profile. »

— 07:48 — « As a data engineer, writing code is just a 10. I mean, a company will expect you that if you are a professional then you can code. »

— 09:43 — « If your basics are strong, if you have made good projects, then it will be very easy for you to make your career transition. »

Category

Educational

Video