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Database Architects vs Data Scientists

Side-by-side · O*NET · BLS · AI-exposure research · Anthropic Economic Index

A factual, source-backed comparison of Database Architects and Data Scientists on the dimensions both occupations carry. Every figure is a position within an independent published dataset — not a verdict on which job is better, safer, or more “future-proof.”

Database Architects Data Scientists
Median pay · BLS OEWS
$135,980
$112,590
Employment · BLS OEWS
64,770
233,440
AI exposure (percentile) · task overlap, not automation
91st pct
98th pct

At a glance

Dimension Database Architects Data Scientists
Median pay $135,980 $112,590
Employment 64,770 233,440
Employment outlook (2024–34) · BLS projection Growing fast (+8.7%) Growing fast (+33.5%)
Annual openings · BLS projection 4,000 23,400
Typical education · O*NET Most of these occupations require a four-year bachelor's degree, but some do not. Most of these occupations require a four-year bachelor's degree, but some do not.
AI exposure · published exposure studies High · 91st pct High · 98th pct
Global GenAI gradient · ILO ISCO-08 · via crosswalk — —
Observed AI use · Anthropic Economic Index — —
Mostly remote-capable · Dingel–Neiman — —

Pay and employment are BLS OEWS estimates; outlook and openings are BLS 2024–2034 projections; AI exposure and observed-use figures come from separate research and reflect exposure and usage, not predictions that either job will disappear. Compare like with like.

Skills

Specific to Database Architects

  • Computers and Electronics
  • Engineering and Technology
  • Reading Comprehension
  • Critical Thinking
  • Complex Problem Solving
  • Judgment and Decision Making
  • Oral Comprehension
  • Written Comprehension

Specific to Data Scientists

    Knowledge, skills & abilities O*NET rates as important for each occupation. “Shared” are common to both; the columns list what is distinctive to each (top by the order O*NET surfaces).

    Tools & technology

    Shared: Data base user interface and query software , Development environment software , Object or component oriented development software , Spreadsheet software , Business intelligence and data analysis software , Presentation software , Data mining software , Web platform development software , Data base management system software , Procedure management software , File versioning software , Operating system software , Project management software , Content workflow software , Application server software .

    Specific to Database Architects

    Specific to Data Scientists

    Full profiles

    This page is a summary. See the complete source-backed profile for Database Architects or Data Scientists — tasks, the full skill graph, tools, work context, preparation, wages by percentile, industries, AI exposure and the AI work map.

    More comparisons

    Related occupations you can place side by side on the same sourced scale.

    Sources for this page

    Every figure above traces to a named public dataset and the exact release below — not hand-written opinion. See the full methodology for what each measure does and does not mean.

    Data compiled June 2, 2026. Figures are estimates, not advice.

    Cite this page
    Plain

    Singulariki. "Database Architects vs Data Scientists." Singulariki: a source-backed encyclopedia of work. Built from O*NET 30.3; BLS Occupational Employment and Wage Statistics (OEWS) May 2024; BLS Employment Projections 2024–2034; Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27); Microsoft “Working with AI” working-with-ai; “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130. Accessed June 7, 2026. https://singulariki.com/compare/database-architects-vs-data-scientists

    APA

    Singulariki. (2026). Database Architects vs Data Scientists. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/compare/database-architects-vs-data-scientists

    BibTeX 
    @misc{singulariki-database-architects-vs-data-scientists,
  title  = {Database Architects vs Data Scientists},
  author = {{Singulariki}},
  year   = {2026},
  note   = {O*NET 30.3; BLS Occupational Employment and Wage Statistics (OEWS) May 2024; BLS Employment Projections 2024–2034; Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27); Microsoft “Working with AI” working-with-ai; “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130. Accessed June 7, 2026},
  url    = {https://singulariki.com/compare/database-architects-vs-data-scientists}
}

    Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.