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

Salary details

The average senior-level / expert Cloud Database Engineer salary lies between USD 105,500 and USD 230,800 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: Nov. 17, 2024

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

The three most common job tag items assiciated with senior-level / expert Cloud Database Engineer job listings are SQL, Security 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:

SQL | 38 jobs Security | 37 jobs AWS | 36 jobs PostgreSQL | 32 jobs Azure | 28 jobs Engineering | 26 jobs Linux | 25 jobs MySQL | 24 jobs Architecture | 23 jobs Computer Science | 23 jobs Oracle | 21 jobs Python | 18 jobs GCP | 17 jobs RDBMS | 16 jobs MongoDB | 14 jobs Kubernetes | 14 jobs Clustering | 14 jobs Testing | 13 jobs Terraform | 11 jobs OpenStack | 11 jobs

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

The three most common job benefits and perks assiciated with senior-level / expert Cloud Database Engineer job listings are Health care, Career development and Competitive pay. 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:

Health care | 17 jobs Career development | 16 jobs Competitive pay | 13 jobs Flex hours | 12 jobs Team events | 10 jobs Flex vacation | 9 jobs Equity / stock options | 8 jobs Startup environment | 7 jobs Insurance | 6 jobs Wellness | 5 jobs Transparency | 5 jobs Salary bonus | 5 jobs Medical leave | 4 jobs 401(k) matching | 2 jobs Unlimited paid time off | 2 jobs Gear | 1 jobs Conferences | 1 jobs Flexible spending account | 1 jobs Fertility benefits | 1 jobs

Salary Composition

In the United States, the salary for a Senior-level/Expert Cloud Database Engineer in AI/ML/Data Science typically comprises a base salary, bonuses, and additional remuneration such as stock options or benefits. The base salary is often the largest component, accounting for approximately 70-80% of the total compensation package. Bonuses, which can be performance-based or company-wide, usually make up about 10-15%. Additional remuneration, including stock options, profit-sharing, or other benefits, can account for the remaining 5-15%.

The composition can vary significantly depending on the region, industry, and company size. For instance, tech hubs like Silicon Valley or Seattle might offer higher base salaries and stock options, while companies in the finance sector might provide substantial bonuses. Larger companies often have more structured compensation packages, whereas startups might offer more equity to attract talent.

Increasing Salary Further

To increase your salary beyond the median of USD 174,312, consider the following strategies:

• Specialization: Develop expertise in niche areas of AI/ML or cloud technologies that are in high demand but have a limited talent pool.
• Leadership Roles: Transition into managerial or leadership positions, such as a Cloud Database Architect or Director of Data Engineering, which typically offer higher salaries.
• Continuous Learning: Stay updated with the latest technologies and trends in AI/ML and cloud computing. This could involve taking advanced courses or obtaining new certifications.
• Networking: Engage with professional networks and communities to learn about new opportunities and negotiate better compensation packages.
• Consulting: Consider freelance consulting or part-time roles that can supplement your income.

Educational Requirements

Most Senior-level/Expert Cloud Database Engineer positions require at least a bachelor's degree in computer science, information technology, or a related field. However, a master's degree or Ph.D. in data science, machine learning, or a related discipline can be advantageous and sometimes preferred. Advanced degrees often provide a deeper understanding of complex algorithms and data structures, which are crucial in AI/ML roles.

Helpful Certifications

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

• AWS Certified Solutions Architect: Demonstrates expertise in designing and deploying scalable systems on AWS.
• Google Professional Data Engineer: Validates your ability to design, build, and operationalize data processing systems.
• Microsoft Certified: Azure Data Engineer Associate: Focuses on implementing data solutions using Azure services.
• Certified Data Management Professional (CDMP): Offers a broad understanding of data management principles.
• Cloudera Certified Data Engineer: Specializes in data engineering on the Cloudera platform.

Required Experience

Typically, a Senior-level/Expert Cloud Database Engineer role requires 5-10 years of experience in database management, cloud computing, and data engineering. Experience with cloud platforms like AWS, Azure, or Google Cloud is essential. Additionally, hands-on experience with database technologies (e.g., SQL, NoSQL), data warehousing, and ETL processes is crucial. Experience in AI/ML projects, particularly those involving large-scale data processing, can be a significant advantage.

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