The Most Underrated Data Career of 2025

Summary

In this video, the speaker explores the growing field of data engineering, highlighting its importance in the modern data landscape. They discuss how data engineers manage and optimize data pipelines, enabling data scientists and analysts to work efficiently with structured data. The speaker shares their personal journey of discovering data engineering, the financial rewards of the role, and the ease of entry into the field. With high demand and accessible learning resources, data engineering is presented as an underrated, high-paying career path for those interested in the data industry.

Takeaways

• 😀 Data engineering is an often underrated career that plays a crucial role in handling and transforming data for companies.
• 😀 Data engineers are responsible for creating, managing, and monitoring data pipelines that ingest, transform, and load data into warehouses, lakes, and BI tools.
• 😀 The role of a data engineer is vital for ensuring data is available in a usable format for analysts and scientists to create reports and models.
• 😀 Data engineering may not be as high-profile as data science or machine learning but it offers great pay and is easy to break into, even without advanced degrees.
• 😀 The demand for data engineers is expected to grow due to the increasing amount of data and the need for more specialized roles in the era of AI and big data.
• 😀 Salaries for data engineers in the US range from $110,000 to $160,000, with a median salary of $130,000, and rapid pay growth is common.
• 😀 You don't need a PhD or master's degree to become a data engineer, with many starting as data analysts or data scientists before transitioning.
• 😀 Key skills for data engineers include proficiency in SQL, Python, and cloud infrastructure, along with experience with tools like Databricks, Snowflake, and Airflow.
• 😀 Data engineers are often described as 'plumbers for data,' optimizing processes that save money, reduce time, and improve overall data infrastructure.
• 😀 Data engineering offers a variety of subroles like database administrators and data analytics engineers, providing opportunities for career growth and specialization.
• 😀 Learning some data engineering skills is beneficial for anyone interested in the data field, as it can enhance your value in adjacent roles such as data science or analytics.

Q & A

What is the main focus of the video script?

The video script focuses on explaining the role of data engineering, highlighting its importance, growth potential, salary expectations, and the skill set required to break into the field.

Why does the speaker believe data engineering is an underrated career in 2025?

The speaker believes data engineering is underrated because it is not as hyped as roles like data science or machine learning, yet it offers excellent salary potential, job stability, and is crucial for enabling data analysis and AI applications.

What role does a data engineer play in a company?

A data engineer is responsible for creating, managing, and monitoring data pipelines, ensuring data is extracted, transformed, and loaded into warehouses or data lakes. They also collaborate with data analysts to make data usable for reports and models.

What are some of the key tools mentioned for data engineering?

Some of the key tools mentioned include SQL, Python, cloud infrastructure, and platforms like Databricks, Snowflake, Airbyte, and Airflow.

How does the salary for a data engineer compare to other data roles?

The salary for a data engineer ranges from $110,000 to $160,000 in the US, with a median salary of $130,000, which is competitive compared to other roles in data science and analytics.

What is the typical career progression for someone in data engineering?

A typical career progression starts from roles like data analyst or business analyst before transitioning into data engineering. Many data engineers build their expertise on the job by learning SQL, Python, and cloud technologies.

What makes the role of a data engineer less glamorous compared to other data roles?

The role of a data engineer is considered less glamorous because it involves more procedural work like maintaining pipelines and handling raw data, as opposed to the more visible tasks of data scientists or machine learning engineers who create models or dashboards.

How did the speaker's mentor influence their career in data engineering?

The speaker's mentor, who was a data engineer, played a crucial role in passing on valuable knowledge and practical skills in data engineering, which helped the speaker grow in their role and eventually earn a promotion.

What are the general requirements to become a data engineer?

The general requirements to become a data engineer include experience with SQL and Python, knowledge of cloud infrastructure for big data management, and familiarity with tools like Databricks and Snowflake. A PhD or master's degree is not typically required.

What are some of the subroles within the field of data engineering?

Some of the subroles within data engineering include database administrators and data analytics engineers. These roles act as bridges between data engineers and other teams like data science or business intelligence.