Salary for Senior-level / Expert Data Architect in United States during 2024

Salary details

The average senior-level / expert Data Architect salary lies between USD 122,000 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. 15, 2024

Salary trend

Top 20 Job Tags for Senior-level / Expert Data Architect roles

The three most common job tag items assiciated with senior-level / expert Data Architect job listings are Architecture, Engineering and Security. 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:

Architecture | 1942 jobs Engineering | 1359 jobs Security | 1314 jobs SQL | 1274 jobs AWS | 1086 jobs Data management | 1032 jobs Azure | 1028 jobs Data governance | 1007 jobs Computer Science | 912 jobs ETL | 904 jobs Python | 853 jobs Pipelines | 783 jobs Data quality | 747 jobs Agile | 715 jobs Big Data | 687 jobs GCP | 621 jobs Machine Learning | 612 jobs Spark | 585 jobs Snowflake | 579 jobs Databricks | 566 jobs

Top 20 Job Perks/Benefits for Senior-level / Expert Data Architect roles

The three most common job benefits and perks assiciated with senior-level / expert Data Architect 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 | 1341 jobs Health care | 844 jobs Flex hours | 654 jobs Competitive pay | 515 jobs Flex vacation | 375 jobs Insurance | 361 jobs Startup environment | 351 jobs Team events | 348 jobs Equity / stock options | 346 jobs Parental leave | 314 jobs Salary bonus | 309 jobs Medical leave | 278 jobs 401(k) matching | 209 jobs Wellness | 205 jobs Fitness / gym | 82 jobs Home office stipend | 74 jobs Transparency | 68 jobs Gear | 60 jobs Unlimited paid time off | 57 jobs Fertility benefits | 51 jobs

Salary Composition

In the United States, the salary composition for a Senior-level or Expert Data Architect in AI/ML/Data Science typically includes a mix of base salary, bonuses, and additional remuneration such as stock options or equity, especially in tech companies. The base salary often constitutes the largest portion, ranging from 70% to 85% of the total compensation package. Bonuses, which can be performance-based or company-wide, usually account for 10% to 20%. Additional remuneration, such as stock options, profit sharing, or other incentives, can make up the remaining 5% to 10%. The exact composition can vary significantly depending on the region, industry, and company size. For instance, tech hubs like Silicon Valley or New York may offer higher base salaries and more substantial equity packages, while smaller companies might offer more in bonuses to attract talent.

Increasing Salary Further

To increase your salary beyond the median of USD 160,000, consider the following strategies:

• Specialization: Develop expertise in niche areas of AI/ML, such as deep learning, natural language processing, or AI ethics, which are in high demand.
• Leadership Roles: Transition into leadership or managerial roles, such as Chief Data Officer or Head of Data Science, which typically offer higher compensation.
• Consulting: Consider consulting roles or freelance opportunities, which can offer higher hourly rates and the flexibility to work with multiple clients.
• Continuous Learning: Stay updated with the latest technologies and methodologies in AI/ML to remain competitive and justify salary increases.

Educational Requirements

Most Senior-level Data Architect positions require at least a bachelor's degree in computer science, data science, information technology, or a related field. However, a master's degree or Ph.D. is often preferred, especially for roles that involve complex data modeling and AI/ML algorithm development. Advanced degrees can provide a deeper understanding of theoretical concepts and practical applications, making candidates more attractive to employers.

Helpful Certifications

While not always mandatory, certain certifications can enhance your credentials and demonstrate expertise:

• Certified Data Management Professional (CDMP)
• AWS Certified Big Data – Specialty
• Google Professional Data Engineer
• Microsoft Certified: Azure Data Scientist Associate
• Cloudera Certified Data Professional

These certifications can validate your skills in data architecture, cloud platforms, and data management, making you a more competitive candidate.

Required Experience

Typically, a Senior-level Data Architect role requires 8 to 12 years of experience in data architecture, data engineering, or related fields. This experience should include a strong background in designing and implementing data solutions, proficiency in data modeling, and familiarity with AI/ML frameworks and tools. Experience in leading projects and teams is also highly valued, as these roles often involve strategic decision-making and collaboration with cross-functional teams.

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