How to Become a Data Engineer in 2024? Data Engineer Complete Roadmap

Summary

In this video, the speaker outlines two roadmaps for becoming a data engineer in 2024: a short-term and long-term approach. The short-term roadmap focuses on mastering essential skills like Python, relational databases (MySQL), cloud platforms (Azure/GCP), and ETL tools (Apache Airflow), ideal for product-based companies and startups. The long-term roadmap involves deeper expertise in data fundamentals, Big Data technologies (Hadoop, Spark), cloud services, streaming tools, machine learning basics, and DevOps practices, aiming for high-paying roles in top MNCs. Both paths offer valuable insights for aspiring data engineers.

Takeaways

• 😀 Focus on mastering one programming language, with Python being highly recommended for data engineers.
• 😀 For short-term career growth, concentrate on relational databases like MySQL and avoid non-relational databases initially.
• 😀 Cloud technologies such as Microsoft Azure or Google Cloud are crucial for data engineers, particularly in their short-term learning journey.
• 😀 To advance, learn and specialize in ETL (Extract, Transform, Load) tools like Apache Airflow and Apache Kafka.
• 😀 Building expertise in tools like DataBricks is essential for long-term career development in data engineering.
• 😀 It’s possible to achieve a 6-8 LPA salary with the short-term roadmap, but 15-20 LPA can be expected with the long-term roadmap after six months of dedicated effort.
• 😀 Time management is key—avoid distractions like social media during your study period to stay focused.
• 😀 There are numerous free resources available on platforms like YouTube, but for those who prefer structured learning, Udemy offers affordable courses.
• 😀 Git is an essential skill for version control and collaboration in coding, and should be mastered as part of the long-term roadmap.
• 😀 Mastering big data tools like Apache Hadoop and Spark, and learning data warehousing technologies like Snowflake, will set you up for advanced career roles.
• 😀 Consistency and dedication are critical—commit to a six-month learning journey to build a competitive skill set and land high-paying roles.

Q & A

What is the main focus of the roadmap in the video?

The roadmap in the video focuses on guiding freshers on how to become a Data Engineer in 2024. It outlines a short-term and long-term strategy for building the necessary skills and preparing for interviews in the Data Engineering field.

What are the two types of roadmaps discussed in the video?

The video discusses two types of roadmaps: the short-term roadmap, which focuses on basic skills to get a job quickly (usually within 3 months), and the long-term roadmap, which focuses on gaining more in-depth knowledge and expertise to land higher-paying roles (around 6 months).

Why is Python recommended over other programming languages for Data Engineering?

Python is recommended because it is an easy-to-learn language with a wide range of libraries and frameworks that support Data Engineering tasks. Python allows for writing concise code, making debugging easier, and is used across many fields, including Data Engineering and Data Science.

What database skills should freshers focus on for the short-term roadmap?

For the short-term roadmap, freshers should focus on mastering relational databases, specifically MySQL. Non-relational databases like MongoDB can be learned later when working at a company that uses them.

What cloud platforms are suggested for beginners to learn?

The video suggests learning either Microsoft Azure or Google Cloud Platform (GCP) for beginners. These platforms are easier to start with compared to AWS, especially for freshers who need free resources for learning.

Why is Microsoft Azure recommended for beginners over AWS?

Microsoft Azure is recommended because it offers more free services for a longer duration compared to AWS, making it easier for freshers to learn without incurring additional costs. Its user interface is also considered easier to navigate.

What ETL or orchestration tools should beginners focus on?

Beginners should focus on modern ETL and orchestration tools like Apache Airflow and Apache Kafka, as older tools like Informatica and Pentaho are becoming less popular. These tools are widely used in new startup environments.

What is the role of Big Data technologies like Hadoop and Spark in the long-term roadmap?

In the long-term roadmap, gaining expertise in Big Data technologies like Hadoop (HDFS, MapReduce) and Spark is important. These technologies are essential for handling large-scale data processing and in-memory computations, which are critical in data engineering roles.

What are the benefits of learning DevOps practices like CI/CD and Terraform?

Learning DevOps practices such as CI/CD (Continuous Integration/Continuous Deployment) helps automate the software development process, making it more efficient. Tools like Terraform are important for automating infrastructure provisioning, saving time, and ensuring consistency in cloud environments.

What is the expected salary range for freshers following the short-term and long-term roadmaps?

Following the short-term roadmap, freshers can expect a salary range of 6 to 8 LPA (Lakhs Per Annum). By following the long-term roadmap and gaining deeper expertise, freshers can target a salary range of 15 to 20 LPA.

How should freshers manage their time and resources while following this roadmap?

Freshers should focus on their studies by avoiding distractions like social media for 3-6 months. They can use free resources like YouTube and affordable platforms like Udemy to learn. The speaker emphasizes staying committed to one technology in each category (programming language, database, cloud, etc.) to avoid overwhelm.