Data Architect Salary in United States during 2024
💰 The median Data Architect Salary in United States during 2024 is USD 160,000
✏️ This salary info is based on 862 individual salaries reported during 2024
Salary details
The average Data Architect salary lies between USD 122,000 and USD 196,500 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.
- Job title
- Data Architect
- Experience
- all levels
- Region
- United States
- Salary year
- 2024
- Sample size
- 862
- Top 10%
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- Top 25%
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- Median
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- Bottom 25%
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- Bottom 10%
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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:Salary trend
Top 20 Job Tags for Data Architect roles
The three most common job tag items assiciated with 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 | 2049 jobs Engineering | 1433 jobs Security | 1378 jobs SQL | 1338 jobs AWS | 1137 jobs Data management | 1093 jobs Azure | 1081 jobs Data governance | 1065 jobs Computer Science | 969 jobs ETL | 950 jobs Python | 899 jobs Pipelines | 807 jobs Data quality | 789 jobs Agile | 751 jobs Big Data | 728 jobs GCP | 647 jobs Machine Learning | 643 jobs Spark | 610 jobs Snowflake | 600 jobs Databricks | 594 jobsTop 20 Job Perks/Benefits for Data Architect roles
The three most common job benefits and perks assiciated with 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 | 1400 jobs Health care | 880 jobs Flex hours | 682 jobs Competitive pay | 541 jobs Flex vacation | 389 jobs Insurance | 374 jobs Startup environment | 372 jobs Team events | 368 jobs Equity / stock options | 367 jobs Salary bonus | 327 jobs Parental leave | 323 jobs Medical leave | 286 jobs Wellness | 217 jobs 401(k) matching | 216 jobs Fitness / gym | 84 jobs Home office stipend | 75 jobs Transparency | 73 jobs Gear | 61 jobs Unlimited paid time off | 58 jobs Conferences | 56 jobsSalary Composition for a Data Architect in AI/ML/Data Science
The salary for a Data Architect in AI/ML/Data Science typically comprises a base salary, performance 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. Performance bonuses can vary significantly, ranging from 10-20% of the base salary, depending on individual and company performance. Additional remuneration, such as stock options, profit-sharing, or other benefits, can make up the remaining 5-10%.
Regional differences can influence these percentages. For instance, in tech hubs like Silicon Valley or New York City, the base salary might be higher, but the cost of living adjustments and competitive market can lead to more substantial bonuses and stock options. Industry also plays a role; tech companies might offer more in stock options, while financial services might provide higher cash bonuses. Company size can affect the package as well, with larger companies often providing more comprehensive benefits and smaller companies offering more equity-based compensation.
Steps to Increase Salary from a Data Architect Position
To increase your salary from a Data Architect position, consider the following strategies:
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Skill Enhancement: Continuously update your skills in emerging technologies and methodologies in AI/ML and data science. Specializing in niche areas like deep learning, natural language processing, or big data analytics can make you more valuable.
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Advanced Education: Pursuing further education, such as a master's or Ph.D. in a related field, can open doors to higher-paying roles.
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Leadership Roles: Transitioning into leadership or managerial roles, such as a Chief Data Officer or Head of Data Science, can significantly increase your earning potential.
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Networking and Industry Engagement: Actively participate in industry conferences, workshops, and seminars to build a strong professional network. This can lead to opportunities in higher-paying companies or roles.
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Negotiation Skills: Improve your negotiation skills to better advocate for higher pay during performance reviews or when switching jobs.
Educational Requirements for a Data Architect Role
Most Data Architect positions require at least a bachelor's degree in computer science, information technology, data science, or a related field. However, a master's degree is often preferred, especially for roles in AI/ML and data science. Advanced degrees provide a deeper understanding of complex data systems and analytical techniques, which are crucial for designing and managing data architectures.
Helpful Certifications for Data Architects
Certifications can enhance your credibility and demonstrate your expertise. Some valuable certifications include:
- Certified Data Management Professional (CDMP)
- AWS Certified Solutions Architect
- Google Professional Data Engineer
- Microsoft Certified: Azure Solutions Architect Expert
- Cloudera Certified Data Professional
These certifications validate your skills in data management, cloud architecture, and data engineering, which are essential for a Data Architect role.
Experience Required for a Data Architect Position
Typically, a Data Architect role requires 5-10 years of experience in data management, data warehousing, or a related field. Experience in designing and implementing complex data systems, as well as proficiency in data modeling, database design, and data integration, is crucial. Experience with cloud platforms and big data technologies is increasingly important in AI/ML and data science roles.
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