Backend Developer
$120,556
avg. annual salary
Data Engineer
pays more on average
Data Engineer
$125,195
avg. annual salary
As the tech industry evolves, the demand for specialized roles continues to grow. Two prominent positions in this landscape are Backend Developers and Data Engineers. Both roles are essential for the development and management of software and data systems. Understanding their salaries, benefits, and career trajectories can help you make informed decisions about your career path. This comparison delves into the salary differences for both professions, explores the benefits each role offers, and outlines future career opportunities. Whether you're considering a career change or just curious about the job market, this guide provides a detailed overview of Backend Developer and Data Engineer salaries in 2025.
Salary by Experience Level
starting salary
starting salary
avg. difference (4%)
Salary Overview
In 2025, the average salary for a Backend Developer is approximately $110,000 per year, while Data Engineers can expect around $120,000 annually. The salary range for Backend Developers typically falls between $85,000 and $140,000, depending on experience and location.
For Data Engineers, the range is between $95,000 and $150,000. Factors such as technical skills, years of experience, and geographic location significantly affect these salary figures.
Benefits
Both Backend Developers and Data Engineers enjoy comprehensive benefits that may include health insurance, retirement plans, and paid time off. Additionally, Data Engineers may receive benefits geared toward advanced training in data analytics tools and technologies, while Backend Developers might have opportunities for continuing education in programming languages and frameworks.
Companies often provide flexible work arrangements, including remote work options, which are increasingly important to today's professionals.
Career Path and Opportunities
Backend Developers often advance to roles such as Senior Developer, Technical Lead, or Software Architect, focusing on the design and architecture of applications. In contrast, Data Engineers typically progress to Data Architect or Data Science roles, leveraging their skills to design complex data systems and analytical tools.
Both career paths offer opportunities in emerging technologies such as AI and machine learning, making them attractive options for the future job market.
Key Skills Required
For Backend Developers, essential skills include proficiency in programming languages like Java, Python, or Ruby, and experience with databases and APIs. Data Engineers need strong skills in SQL, data warehousing, and tools like Apache Spark or Hadoop.
Continuous learning and adaptation to new technologies are crucial for success in both fields.
Conclusion
When comparing the salaries of Backend Developers and Data Engineers, both roles provide lucrative career options with unique benefits and opportunities. Deciding which path to pursue should involve consideration of personal interests, strengths, and market demand.
Detailed Comparison: Backend Developer vs Data Engineer (Practical View)
Backend developers and data engineers both work on servers and pipelines, but they solve different problems. Backend developers focus on building APIs, microservices, and business logic.
Typical tech: Java, Node. js, Python, PostgreSQL, Redis.
In the U. S.
, mid-level backend dev salary ranges often sit between $95,000–$145,000; senior roles reach $150,000–$220,000 plus 5–15% in bonuses or equity at startups.
Data engineers design ETL pipelines, maintain data warehouses, and optimize data flow for analytics. Typical tech: Spark, Kafka, Airflow, Snowflake, BigQuery.
Mid-level data engineer pay commonly ranges $105,000–$155,000; senior roles can reach $160,000–$240,000 with similar bonus/equity mixes. Location matters: San Francisco and NYC can push totals 20–35% higher than Midwest markets.
In short, data engineers often command slightly higher base pay due to demand for large-scale data skills; backend developers can match total comp when they own product-critical systems.
Actionable takeaway: match your tech focus to high-paying industries (fintech, adtech, cloud) and quantify system impact during negotiation.
Key Factors to Consider When Comparing Salaries
When comparing offers, evaluate these concrete factors:
- •Location and cost of living: remote roles often pay 5–10% less than in-office SF/NYC roles; adjust expectations accordingly.
- •Company size and stage: large tech firms frequently pay 20–40% above market for senior roles; late-stage startups compensate with 5–20% equity instead of higher base pay.
- •Skill scarcity: expertise in Spark, Snowflake, or distributed systems can add 8–15% to base pay; niche language skills add less.
- •Role scope: owning data platform or service-level uptime typically yields higher pay than narrow feature work.
- •Compensation mix: compare base vs bonus vs equity; total compensation can vary by 10–30% even with similar bases.
- •Market demand: industries like finance, adtech, and cloud services tend to have the highest salaries.
Actionable takeaway: create a scorecard weighting these factors, then negotiate by quantifying scope, availability, and measurable impact.