2025 Data Engineering Tech Salary Guide

As of 2025, mid-level Data Engineers can expect to earn between $117,873 and $150,488. Senior-level Data Engineers can earn between $140,311 and $174,892. Salaries in tech hubs, such as San Francisco and Seattle, tend to be higher than the national average. 

The Data Engineering job with the highest salary is Computer Vision Engineer, with senior-level positions reaching up to $218,750.

For a Data Engineer with 5 years of experience in 2025, the average salary ranges from $125,128 to $157,222 for mid-level positions.  

This figure can vary significantly depending on geographic location, particularly in tech hubs like San Francisco, Seattle, and Silicon Valley, where salaries can be higher than the national average.

Data Engineering salaries did increase in 2024. The average salary for a senior data engineer in the United States ranges from $144,519 to $177,289. 

In 2025, Data Engineers are expected to have the following salary ranges: for mid-level positions, the salary can range from $125,128 to $157,222, while for senior-level positions, it can range from $144,519 to $177,289.

In 2024, the growth in Data Engineering was significantly influenced by the surge in demand for AI skills. Job postings related to generative AI skills saw a 267% increase year-over-year from the start of 2023 through February 2024. This demand impacted tech jobs broadly, with more than 10% of tech job postings in some months requiring AI skills. The emphasis on AI also drove high salaries for roles related to Artificial Intelligence and Machine Learning. 

To pursue a career in Data Engineering in 2025, you will need to master a blend of emerging and foundational technical skills as well as enhance your proficiency in key data technologies. Here are some of the updated skills essential for a successful career in this field: 

• Advanced Programming Skills: While proficiency in Python and SQL remains crucial, gaining skills in newer languages and frameworks such as Scala for Spark and Java for Hadoop can be advantageous. 

• Data Management and Storage Solutions: There is a growing demand for expertise in cloud-based data warehousing solutions. Familiarity with platforms like Amazon Redshift, Google BigQuery, and Snowflake has become increasingly important. 

• Cloud Technologies: Understanding and working knowledge of cloud services such as AWS, Azure, or Google Cloud is essential, given the industry's shift toward multi-cloud environments. 

• Data Pipeline Automation: Experience in building robust ETL pipelines is crucial. Knowledge of orchestration tools such as Apache Airflow for workflow management is a valuable asset. 

• Real-time Data Processing: With a shift towards real-time data processing, skills in tools like Apache Kafka for stream processing and Apache Flink are becoming more important. 

• Emerging Technologies: Keeping current with evolving technologies like Databricks for unified data analytics and PySpark for handling large datasets is important. 

By building these skills, you will be well-equipped to tackle the challenges of modern data infrastructure and take advantage of opportunities in this rapidly evolving field.

The long-term prospects for Data Engineering in 2025 remain robust, driven by several factors: 

• Impact of AI and Machine Learning: AI continues to be a central topic in the tech industry, fueling the growth of job opportunities. Professionals with skills in AI and Data Engineering are in high demand as businesses integrate AI solutions into their operations. This demand is reflected in increased job postings and the creation of new roles dedicated to AI infrastructure. 

• Growing AI Skill Requirements: The demand for AI-related skills has surged by 267% year over year, highlighting the increasing need for professionals who can navigate and implement AI technologies. This growth in AI skills is not limited to tech-specific companies, expanding the prospects for Data Engineers across various sectors. 

• High Compensation for AI Skills: Due to the scarcity of talent, businesses in North America are investing significantly in AI capabilities, offering top salaries for AI-related skills. Data Engineers with expertise in AI systems can command considerably higher compensation, reinforcing the value of their skill set in the current market. 
   

These insights underscore the ongoing and expanding role Data Engineering plays within the tech industry, particularly as it intersects with AI and Machine Learning advancements. 

There are significant opportunities for growth in the Data Engineering industry as we move into 2025. The demand for data professionals remains high, with data scientists and tech support specialists being among the roles with the highest number of job postings.