Data Engineer
$110,000
avg. annual salary
Python Developer
pays more on average
Python Developer
$110,230
avg. annual salary
As the tech industry evolves, understanding the salary landscape for various roles is essential for career planning. Two important positions in the data and software sectors are Data Engineers and Python Developers. While both roles involve working with data and software development, they have distinct responsibilities, skill sets, and salary expectations. In 2025, the demand for both Data Engineers and Python Developers remains high, leading to competitive salary packages. This guide compares their average salaries, job benefits, and career trajectories, helping you make informed decisions about your career in technology. Whether you are considering a job as a Data Engineer or a Python Developer, this information aims to provide clarity on what you can expect in terms of compensation and growth opportunities.
Salary by Experience Level
starting salary
starting salary
avg. difference (0%)
Average Salary Overview
In 2025, the average salary for a Data Engineer is approximately $120,000 per year, with a typical range from $100,000 to $140,000. On the other hand, Python Developers earn an average salary of about $115,000, with a range of $95,000 to $135,000.
Both roles are well-compensated due to the specialized skills and knowledge required. However, the Data Engineer's role often commands a slightly higher salary due to the growing importance of data management and engineering in business decision-making.
Salary by Experience Level
For entry-level positions, Data Engineers can expect to earn between $80,000 and $95,000, while entry-level Python Developers typically earn between $75,000 and $90,000. As professionals advance to mid-level positions, Data Engineers see salaries ranging from $110,000 to $130,000, compared to mid-level Python Developers, who earn between $100,000 and $120,000.
Senior-level roles present the highest compensation, with Data Engineers making between $140,000 and $160,000, while Python Developers can earn up to $150,000.
Benefits Comparison
Both Data Engineers and Python Developers typically enjoy a robust benefits package that includes health insurance, retirement plans, and paid time off. Additionally, many tech companies offer perks such as remote work options, flexible schedules, and professional development opportunities.
However, Data Engineers may have access to specific training programs aimed at enhancing their data management skills, which can further their career growth.
Career Path and Opportunities
Data Engineers often start out as junior data analysts or software engineers before specializing in data management. They can advance to roles such as Data Architect or Analytics Engineer.
Python Developers, meanwhile, frequently begin as software developers or web developers, with opportunities to transition into roles like Machine Learning Engineer or Software Architect. Both career paths offer strong growth potential, with increasing demand for skilled professionals in both areas.
Job Market Trends
The job market for Data Engineers and Python Developers is expected to continue growing, with a projected increase in demand for data skills and programming languages. As companies increasingly rely on data-driven decisions, Data Engineers will be pivotal.
Conversely, Python Developers are also seeing remarkable growth due to Python's versatility, especially in fields like data science and web development.
Detailed Comparison: Data Engineer vs Python Developer (2025)
### Overview In 2025 the average U. S.
on-site base pay typically sits around: Data Engineer $110k–$160k (median ≈ $125k); Python Developer $95k–$140k (median ≈ $110k). Remote roles compress location differences by ~5–10%.
### What drives pay differences
- •Technical scope: Data engineers who own ETL, streaming, and distributed systems (Spark, Kafka) often earn 10–20% more than general Python developers. Example: a Senior Data Engineer with Spark + AWS Glue can command $140k–$180k.
- •Tool specialization: Cloud certifications (AWS/GCP/Azure) add roughly 8–15% to offers. Experience with Terraform/CI pipelines adds another 5–8%.
- •Industry: Finance and adtech pay premiums of 10–25%; nonprofits and small education shops pay 10–20% less.
### Typical city examples (base pay medians)
- •San Francisco: Data Engineer $150k, Python Developer $135k
- •New York: Data Engineer $140k, Python Developer $125k
- •Austin: Data Engineer $120k, Python Developer $105k
### Senior/Lead roles
- •Staff Data Engineer: $160k–$220k
- •Lead Python Developer: $140k–$200k
### Actionable takeaways
- •Want top pay quickly? Focus on cloud + distributed systems (Spark/Kafka) and target finance/adtech.
- •Prefer Python dev path? Add backend frameworks (Django), async I/O, and system design to reach senior pay bands.