Salary for Senior-level / Expert Cloud Engineer in United States during 2024

Salary details

The average senior-level / expert Cloud Engineer salary lies between USD 130,000 and USD 198,000 in the United States. It represents the overall compensation/gross salary amount for the working year (before deductions like social security, taxes and other contributions), not including equity/stock options or similar benefits.

Region represents the primary country of residence of an employee during the year (or residence for tax purposes). All data shown are full-time equivalent (FTE) salaries. Part-time salary information has been extrapolated to its FTE value.

Last updated: Dec. 22, 2024

Top 20 Job Tags for Senior-level / Expert Cloud Engineer roles

The three most common job tag items assiciated with senior-level / expert Cloud Engineer job listings are Python, Engineering and AWS. Below you find a list of the 20 most occuring job tags in 2024 and the number of open jobs that where associated with them during that period:

Python | 113 jobs Engineering | 110 jobs AWS | 99 jobs Security | 98 jobs Machine Learning | 96 jobs Azure | 90 jobs Architecture | 80 jobs Terraform | 78 jobs Computer Science | 74 jobs Docker | 72 jobs DevOps | 71 jobs CI/CD | 70 jobs Kubernetes | 68 jobs GCP | 62 jobs Agile | 62 jobs Pipelines | 62 jobs Java | 41 jobs Jenkins | 38 jobs GitHub | 37 jobs SQL | 36 jobs

Top 20 Job Perks/Benefits for Senior-level / Expert Cloud Engineer roles

The three most common job benefits and perks assiciated with senior-level / expert Cloud Engineer job listings are Career development, Health care and Flex hours. Below you find a list of the 20 most occuring job perks or benefits in 2024 and the number of open jobs that where offering them during that period:

Career development | 114 jobs Health care | 48 jobs Flex hours | 40 jobs Team events | 33 jobs Equity / stock options | 31 jobs Startup environment | 31 jobs Competitive pay | 31 jobs Salary bonus | 26 jobs Flex vacation | 25 jobs Parental leave | 22 jobs Insurance | 20 jobs Medical leave | 15 jobs 401(k) matching | 13 jobs Wellness | 9 jobs Transparency | 8 jobs Flexible spending account | 8 jobs Conferences | 7 jobs Gear | 6 jobs Relocation support | 5 jobs Flat hierarchy | 3 jobs

Salary Composition

In the United States, the salary composition for a Senior-level or Expert Cloud Engineer in AI/ML/Data Science typically includes a base salary, performance bonuses, and additional remuneration such as stock options or equity, especially in tech companies. The base salary often constitutes the majority of the total compensation package, ranging from 70% to 85%. Performance bonuses can vary significantly, often comprising 10% to 20% of the total compensation, depending on the company's performance and individual achievements. Additional remuneration, such as stock options, can make up 5% to 15% of the total package, particularly in larger tech firms or startups. The exact composition can vary based on the region, with tech hubs like Silicon Valley offering higher base salaries and equity options, while other regions might offer more balanced packages. Industry and company size also play a role, with larger companies typically providing more comprehensive benefits and bonuses.

Increasing Salary Further

To increase your salary beyond the median of USD 165,150, consider pursuing leadership roles such as Cloud Architect or Director of Cloud Engineering, which often come with higher compensation. Specializing in niche areas within AI/ML, such as natural language processing or computer vision, can also command higher salaries. Additionally, gaining expertise in emerging technologies like quantum computing or edge AI can set you apart. Networking within industry circles, attending conferences, and contributing to open-source projects can enhance your visibility and lead to higher-paying opportunities. Negotiating your salary based on market research and leveraging offers from other companies can also be effective strategies.

Educational Requirements

Most Senior-level Cloud Engineer positions in AI/ML/Data Science require at least a bachelor's degree in computer science, engineering, or a related field. However, a master's degree or Ph.D. in a specialized area such as data science, machine learning, or cloud computing can be advantageous and sometimes preferred. Advanced degrees often provide a deeper understanding of complex algorithms and systems, which is crucial for high-level roles. Continuous learning through online courses and workshops is also important to keep up with the rapidly evolving field.

Helpful Certifications

Certifications can significantly enhance your credentials and demonstrate your expertise to potential employers. Some valuable certifications include:

• AWS Certified Solutions Architect – Professional: Validates advanced technical skills and experience in designing distributed applications and systems on the AWS platform.
• Google Professional Cloud Architect: Demonstrates the ability to design, develop, and manage robust, secure, scalable, and dynamic solutions to drive business objectives.
• Microsoft Certified: Azure Solutions Architect Expert: Confirms expertise in designing and implementing solutions that run on Microsoft Azure.
• Certified Kubernetes Administrator (CKA): Useful for roles involving container orchestration and management.
• Certified Data Scientist (CDS): While not cloud-specific, it can be beneficial for roles that blend data science with cloud engineering.

Required Experience

Typically, a Senior-level Cloud Engineer in AI/ML/Data Science is expected to have at least 5 to 10 years of experience in cloud computing, with a strong background in AI/ML technologies. Experience in designing and deploying scalable cloud solutions, managing cloud infrastructure, and optimizing cloud costs is crucial. Familiarity with multiple cloud platforms (AWS, Azure, Google Cloud) and proficiency in programming languages such as Python, Java, or Scala are often required. Experience in leading projects and teams can also be a significant advantage.

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