Salary for Senior-level / Expert Data Architect during 2024

💰 The median Salary for Senior-level / Expert Data Architect during 2024 is USD 154,600

✏️ This salary info is based on 978 individual salaries reported during 2024

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Salary details

The average senior-level / expert Data Architect salary lies between USD 117,000 and USD 193,000 globally. 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
Senior-level / Expert
Region
global/worldwide
Salary year
2024
Sample size
978
Top 10%
$ 241,600
Top 25%
$ 193,000
Median
$ 154,600
Bottom 25%
$ 117,000
Bottom 10%
$ 93,750

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 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 | 1967 jobs Engineering | 1376 jobs Security | 1335 jobs SQL | 1287 jobs AWS | 1100 jobs Data management | 1046 jobs Azure | 1045 jobs Data governance | 1022 jobs Computer Science | 921 jobs ETL | 915 jobs Python | 861 jobs Pipelines | 789 jobs Data quality | 756 jobs Agile | 723 jobs Big Data | 694 jobs GCP | 627 jobs Machine Learning | 622 jobs Spark | 591 jobs Snowflake | 585 jobs Databricks | 572 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 | 1356 jobs Health care | 856 jobs Flex hours | 661 jobs Competitive pay | 522 jobs Flex vacation | 382 jobs Insurance | 366 jobs Equity / stock options | 352 jobs Startup environment | 352 jobs Team events | 352 jobs Parental leave | 322 jobs Salary bonus | 317 jobs Medical leave | 285 jobs 401(k) matching | 214 jobs Wellness | 208 jobs Fitness / gym | 82 jobs Home office stipend | 75 jobs Transparency | 70 jobs Gear | 60 jobs Unlimited paid time off | 58 jobs Fertility benefits | 51 jobs

Salary Composition

The salary for a Senior-level or Expert Data Architect in AI/ML/Data Science typically comprises several components. The fixed base salary is the largest portion, often accounting for 70-80% of the total compensation package. Bonuses, which can be performance-based or tied to company profits, usually make up 10-20%. Additional remuneration might include stock options, especially in tech companies, and other benefits like health insurance, retirement contributions, and paid time off. The exact composition can vary significantly depending on the region, industry, and company size. For instance, tech hubs like Silicon Valley or New York might offer higher base salaries and stock options, while companies in other regions might focus more on bonuses and benefits.

Increasing Salary Further

To increase your salary beyond the median for this role, consider the following strategies:

  • Specialization: Develop expertise in a niche area of AI/ML or Data Science that is in high demand but has a limited talent pool.
  • Leadership Roles: Transition into roles that involve leading teams or projects, such as Chief Data Officer or Head of Data Science.
  • Consulting: Offer your expertise as a consultant, which can command higher hourly rates and provide diverse experiences.
  • Continuous Learning: Stay updated with the latest technologies and methodologies in AI/ML, which can make you more valuable to employers.

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 systems and advanced analytics. These advanced degrees provide a deeper understanding of data architecture principles and the ability to handle large-scale data environments.

Helpful Certifications

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

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

These certifications validate your skills in data management, cloud platforms, and data engineering, making you a more attractive candidate.

Required Experience

Typically, a Senior-level Data Architect role requires 8-10 years of experience in data architecture, data management, or related fields. This experience should include designing and implementing data solutions, working with large datasets, and using data modeling tools. Experience in leading projects and teams is also highly valued, as these roles often involve strategic decision-making and collaboration across departments.

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