What factors influence the salaries of cloud engineers and data engineers?

Several factors influence salaries, including years of experience, geographic location, skill sets, and the size of the company. Generally, cloud engineers can command higher salaries due to the specialized nature of their work.

Are there similar career paths for cloud engineers and data engineers?

Yes, both roles have overlapping skills and can transition into one another. For instance, a cloud engineer may become a data engineer by acquiring data analytics skills, while a data engineer can pivot toward cloud engineering by developing expertise in cloud platforms.

What certifications can enhance a cloud engineer's or data engineer's salary?

Certifications can significantly boost salaries for both roles. For cloud engineers, certifications from AWS, Azure, or Google Cloud are valuable. Data engineers benefit from certifications in data analytics, machine learning, or big data technologies.

Is job security higher for cloud engineers compared to data engineers?

Both fields are experiencing high demand, leading to strong job security. However, cloud engineers may enjoy slightly better job stability due to the growing reliance on cloud infrastructure across industries.

What should someone consider when choosing between becoming a cloud engineer or a data engineer?

Consider your interests and strengths. If you're more inclined towards network and systems management, cloud engineering might suit you better. If you enjoy working with data, analysis, and databases, a career as a data engineer could be more fulfilling.

Can remote work opportunities differ between cloud engineers and data engineers?

While both roles offer remote work opportunities, cloud engineers may find more positions requiring on-site work for infrastructure management. Data engineers, with a focus on data analytics, often have greater flexibility for remote roles.

What industries typically hire cloud engineers and data engineers?

Cloud engineers are commonly found in tech firms, financial services, and healthcare industries. Data engineers are sought in sectors like retail, healthcare, and any business that relies on data analytics for decision-making.

Complete Cloud Engineer vs Data Engineer Salary Comparison (2026)

Quick Comparison

Cloud Engineer

$125,722

avg. annual salary

Data Engineer
pays more on average

Data Engineer

$130,278

avg. annual salary

In the rapidly evolving tech landscape, cloud engineers and data engineers play critical roles in managing and optimizing cloud services and data analytics. Both professions are in high demand, leading to competitive salaries, yet their compensation varies based on factors like experience, location, and skill sets. Understanding these differences can help you make an informed decision about your career path or salary negotiations. In this guide, we will delve into the salaries, benefits, and career trajectories of cloud engineers and data engineers, helping you assess which role aligns best with your aspirations and financial goals.

Salary by Experience Level

Cloud Engineer Entry

$85,167

starting salary

Data Engineer Entry

$88,253

starting salary

Salary Difference

$4,555

avg. difference (4%)

Salary Overview

As of 2025, the average salary for a cloud engineer is approximately $125,000, with salaries ranging from $95,000 to $160,000 depending on experience and location. In contrast, the average salary for data engineers is about $115,000, with a range of $85,000 to $150,000.

The higher salary for cloud engineers can often be attributed to their specialized skills in cloud computing and infrastructure management.

Benefits

Both cloud engineers and data engineers receive attractive benefits, including health insurance, retirement plans, and paid time off. Cloud engineers may also benefit from bonuses tied to project completions and workload management.

Data engineers, on the other hand, often enjoy perks associated with data-driven projects, such as attending tech conferences or training sessions to enhance their analytics skills.

Career Paths

Cloud engineers generally advance to roles such as Cloud Architect or DevOps Engineer, focusing on high-level infrastructure design and system integration. Data engineers can progress to positions like Data Architect or Data Scientist, which involve more complex data modeling and analysis responsibilities.

Both career paths offer opportunities for continuous learning and growth, driven by advancements in technology.

Skills Required

Cloud engineers typically need expertise in cloud platforms like AWS, Azure, or Google Cloud, along with networking and security skills. Data engineers require strong programming skills in languages like Python or Scala, proficiency in database management systems, and knowledge of data warehousing concepts.

Both roles demand problem-solving abilities and a solid understanding of their respective domains.

Job Outlook

According to industry forecasts, the demand for both cloud engineers and data engineers is expected to grow significantly. As businesses increasingly shift toward cloud solutions and data-driven decision-making, these roles will continue to be crucial in tech development.

This growth means robust job security and numerous opportunities for professionals in both fields.

Detailed Comparison: Cloud Engineer vs Data Engineer Salaries

Overview

•In the U.S., typical base salary ranges: Cloud Engineer $100,000–$160,000; Data Engineer $95,000–$150,000. Mid-career medians cluster around $130,000 for cloud and $120,000 for data.

Compensation components

•Base pay: Cloud roles often pay 5%–10% more at the same level due to platform expertise demand.
•Equity and bonuses: In tech hubs, cloud engineers commonly receive 10%–25% of total comp in stock; data engineers typically receive 5%–20%.

By level (example figures)

•Entry (0–2 years): Cloud $70k–$95k; Data $80k–$100k.
•Mid (3–6 years): Cloud $110k–$140k; Data $100k–$130k.
•Senior/Lead: Both can exceed $180k base; total comp $200k–$350k depending on equity.

Factors that change pay

•Location: SF/NYC add ~20%–40%; remote roles vary by company.
•Skill premium: AWS/GCP/Azure certification, Kubernetes, and Terraform can raise pay by 5%–15%; Spark/Kafka/ETL experience adds 5%–12%.
•Industry: Finance and ad tech often pay 10%–30% above average.

Actionable takeaways

•Target certifications and list them on your resume.
•Use local market data when negotiating; ask for a 10%–15% increase if you bring cross-domain skills (cloud + data).

Frequently Asked Questions

Ready to negotiate your salary? Use our salary calculator to determine your market value.