Data Architect Salary Guide

Data Architects design, build, and maintain scalable data frameworks that enable analytics and operational systems. They define data models, integration patterns, governance standards, and platform choices (cloud/on-prem) to ensure data quality, accessibility, security, and performance across the organization.

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What is the average Data Architect salary?

Entry Level

$110,000 - $140,000

Mid Level

$140,000 - $180,000

Senior Level

$180,000 - $240,000+

How does Data Architect salary grow with experience?

$100,000 - $130,000
0-2
$130,000 - $160,000
3-5
$160,000 - $200,000
6-9
$190,000 - $250,000++
10+
Base (min)
Top of range (max)
Max: $250k

Data Architect salary by location

San Francisco Bay Area (CA)$170,000 - $250,000+
New York City (NY)$160,000 - $240,000
Seattle (WA)$155,000 - $230,000
Austin (TX)$130,000 - $200,000
Remote (U.S.)$120,000 - $210,000
Base (min)
Top of range (max)

What factors affect a Data Architect's salary?

  • Technical specialization (cloud platforms, big data stacks, specific databases)
  • Industry and business domain (finance, healthcare, and high-frequency trading often pay more)
  • Company size and funding stage (large tech firms and well-funded startups typically offer higher pay)
  • Location and remote/onsite arrangements
  • Certifications, security clearance, and leadership/architecture ownership experience

How to compare Data Architect pay figures

The generated ranges in this guide have not been independently source-verified. Check the underlying occupation, location and data period before using a range as a market benchmark. Keep the original source alongside any figure you save. A page updated recently can still contain wages measured in an earlier year, and a broad occupational category may cover several different job titles.

Compare the work as well as the title

Read a vacancy's responsibilities, required experience, working hours and location before placing it beside another role. Two positions called Data Architect can have different scope. Record the duties you would own, the team or customers you would support, and any supervisory expectations. Use those details to decide whether a comparison is relevant instead of assuming that a matching title means matching pay.

Keep compensation definitions consistent

Confirm the currency and whether a figure is hourly, monthly or annual. Check the paid hours before converting between periods. Separate guaranteed base pay from bonuses, commissions, overtime, equity and benefits. Ask which parts are guaranteed and which depend on targets, company results or vesting conditions. Compare the same components across offers; a total-compensation figure and a base-salary figure answer different questions.

Identify the statistic too. A median divides the measured workforce into two equal halves. A percentile describes a point in that distribution; it does not automatically describe an entry-level or senior employee. Do not turn national survey percentiles into a personal experience-based pay prediction. Use local, role-relevant evidence when it is available and record any mismatch in coverage.

Build a comparison you can check later

For each job listing, survey or offer, save the role, responsibilities, location, currency, pay period, compensation components, source link and date checked. Mark missing information as unknown. Keep the employer's stated range separate from any expectation you calculate yourself. If the figures differ, first check their definitions and scope rather than averaging incompatible numbers into a new estimate.

When discussing an offer, prepare clear examples of the responsibilities and results you can support with your experience. Ask the recruiter about the role's level, the approved range and how the package is structured. Keep those answers with your comparison so you can assess the offer using confirmed information. This guide gives you questions to investigate; the employer's written terms establish the actual package being offered.

Read the salary source and comparison checklist

Frequently Asked Questions About Data Architect Salaries

What is the average salary for a Data Architect in the US?

On average US Data Architects earn between $140,000 and $200,000 annually, with entry roles near $110k–$140k and senior positions often exceeding $180k–$240k depending on location and industry.

Which skills most increase a Data Architect's salary?

Expertise in cloud platforms (AWS/Azure/GCP), data modeling, data governance, big data technologies (Spark, Kafka), and experience with architecture patterns and leadership typically lead to higher pay.

How does location impact Data Architect pay?

Location strongly affects pay: major tech hubs like the Bay Area, New York, and Seattle pay a premium (often 15–40% above national averages), while smaller markets and some remote roles pay closer to national medians.

What experience level is required to become a senior Data Architect?

Senior Data Architects commonly have 8–12+ years of relevant data engineering/architecture experience, proven delivery of enterprise-scale solutions, and often prior leadership or cross-functional architecture ownership.

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