Skills it runs on
The capabilities O*NET rates most important for this occupation — the human ground the work is built on.
See all skills →Data Warehousing Specialists
Occupation · SOC 15-1243.01
Design, model, or implement corporate data warehousing activities. Program and configure warehouses of database information and provide support to warehouse users.
Also called: Data Warehouse Analyst · Data Warehouse Solution Architect · Analytics Manager · Big Data Engineer · Data Integrity Specialist · Data Management Engineer · Data Management Manager · Data Management Specialist · Data Migration Specialist · Data Quality Analyst · Data Specialist · Data Storage Specialist
Job family: Computer and Mathematical Occupations
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/roles/role-15-1243-01/context.md directly.
AI work map
A fast read on where AI already shows up in this occupation, where it stays a copilot, where humans remain in the loop, and what the labor market is doing. Built from observed Claude.ai conversations mapped to O*NET tasks and from published research — measures of usage and exposure, not advice or predictions that the job is going away.
Market signal
Independent published positions, read together — not a forecast.
- Growing fast employment outlook (+8.7% by 2034)
- 4,000 openings/yr
- High AI exposure
- Median pay $135,980/yr
98th-percentile task overlap — yet about 4,000 openings a year (+8.7% projected, BLS) . What exposure means →
AI & job outlook
What today's research says about this occupation's exposure to AI, how AI is actually being used in it, and where employment is headed. These are positions within published studies — measures of exposure and usage, not predictions that this job will disappear.
Exposure to current AI
Each study uses its own scale, so the raw scores are not comparable across rows — the percentile (this job's rank among all U.S. occupations with data) is the comparable figure, and sizes the bars.
| Measure | Rank vs all occupations | Percentile | Score |
|---|---|---|---|
| LLM task exposure, γ (OpenAI / Eloundou) High | 95th | 1.0 | |
| AI assistant applicability (Microsoft) High | 91st | 0.3 |
OpenAI's exposure study scores tasks three ways: with a language model alone (α 0.9), with simple added tooling (β 0.9), and including AI-powered software (γ 1.0). Higher means more of the job's tasks could be done at least twice as fast — not that they will be automated away.
How AI is actually used in this job
Among measured AI assistant conversations mapped to this occupation (Anthropic Economic Index, 2026-01-15), these task types came up most. These are shares of observed AI conversations — not shares of the job, of worker time, or of what could be automated.
| Write new programs or modify existing programs to meet customer requirements, using current programming languages and technologies. | 31.0% | |
| Create supporting documentation, such as metadata and diagrams of entity relationships, business processes, and process flow. | 8.6% | |
| Perform system analysis, data analysis or programming, using a variety of computer languages and procedures. | 5.6% | |
| Implement business rules via stored procedures, middleware, or other technologies. | 2.1% | |
| Map data between source systems, data warehouses, and data marts. | 1.7% | |
| Design and implement warehouse database structures. | 1.6% |
Job outlook
Independent U.S. Bureau of Labor Statistics employment projection for 2024–2034 — a labor-market forecast, not an AI-impact forecast.
| Outlook | Growing fast · +8.7% by 2034 |
| Projected annual openings | 4,000 |
| Employment 2024 → 2034 | 66,900 → 72,700 |
“Annual openings” counts new jobs plus replacements for workers who leave the occupation, so it can be large even when growth is modest.
Tasks
All 18 tasks O*NET lists for this occupation, ordered by importance. Each links to its own page with AI-exposure and observed-use detail.
- Develop data warehouse process models, including sourcing, loading, transformation, and extraction. Core · importance 4.4
- Verify the structure, accuracy, or quality of warehouse data. Core · importance 4.4
- Map data between source systems, data warehouses, and data marts. Core · importance 4.2
- Develop and implement data extraction procedures from other systems, such as administration, billing, or claims. Core · importance 4.1
- Design and implement warehouse database structures. Core · importance 4.1
- Develop or maintain standards, such as organization, structure, or nomenclature, for the design of data warehouse elements, such as data architectures, models, tools, and databases. Core · importance 4.0
- Provide or coordinate troubleshooting support for data warehouses. Core · importance 3.9
- Write new programs or modify existing programs to meet customer requirements, using current programming languages and technologies. Core · importance 3.9
- Design, implement, or operate comprehensive data warehouse systems to balance optimization of data access with batch loading and resource utilization factors, according to customer requirements. Core · importance 3.9
- Perform system analysis, data analysis or programming, using a variety of computer languages and procedures. Core · importance 3.8
- Create supporting documentation, such as metadata and diagrams of entity relationships, business processes, and process flow. Core · importance 3.8
- Create or implement metadata processes and frameworks. Core · importance 3.7
- Review designs, codes, test plans, or documentation to ensure quality. Core · importance 3.6
- Create plans, test files, and scripts for data warehouse testing, ranging from unit to integration testing. Core · importance 3.6
- Select methods, techniques, or criteria for data warehousing evaluative procedures. Core · importance 3.6
- Implement business rules via stored procedures, middleware, or other technologies. Core · importance 3.5
- Prepare functional or technical documentation for data warehouses. Core · importance 3.3
- Test software systems or applications for software enhancements or new products. Core · importance 3.1
Work activities
- Test software performance.
- Evaluate project designs to determine adequacy or feasibility.
- Troubleshoot issues with computer applications or systems.
- Document operational procedures.
- Modify software programs to improve performance.
- Design software applications.
- Write computer programming code.
- Evaluate data quality.
- Develop performance metrics or standards related to information technology.
- Analyze data to identify trends or relationships among variables.
- Develop diagrams or flow charts of system operation.
- Apply new technologies to improve work processes.
- Apply information technology to solve business or other applied problems.
- Develop procedures for data management.
- Create databases to store electronic data.
- Develop testing routines or procedures.
- Develop models of information or communications systems.
Knowledge, skills & abilities
O*NET importance rating, from 1 (not important) to 5 (extremely important).
Knowledge
| Computers and Electronics | 4.3 | |
| Mathematics | 3.2 | |
| English Language | 3.2 | |
| Design | 3.0 | |
| Engineering and Technology | 2.9 |
Essential skills
| Reading Comprehension | 3.9 | |
| Critical Thinking | 3.9 | |
| Active Listening | 3.5 | |
| Speaking | 3.4 | |
| Writing | 3.3 | |
| Mathematics | 3.0 | |
| Active Learning | 3.0 | |
| Monitoring | 2.9 |
Abilities
| Written Comprehension | 3.9 | |
| Information Ordering | 3.9 | |
| Oral Comprehension | 3.8 | |
| Deductive Reasoning | 3.8 | |
| Inductive Reasoning | 3.8 | |
| Near Vision | 3.6 | |
| Oral Expression | 3.5 | |
| Written Expression | 3.5 | |
| Category Flexibility | 3.5 | |
| Speech Recognition | 3.5 | |
| Problem Sensitivity | 3.4 | |
| Speech Clarity | 3.4 | |
| Fluency of Ideas | 3.1 | |
| Mathematical Reasoning | 3.1 | |
| Originality | 3.0 | |
| Number Facility | 3.0 | |
| Flexibility of Closure | 3.0 | |
| Selective Attention | 3.0 |
Transferable skills
| Programming | 3.8 | |
| Complex Problem Solving | 3.6 | |
| Systems Analysis | 3.5 | |
| Judgment and Decision Making | 3.4 | |
| Systems Evaluation | 3.3 | |
| Coordination | 3.1 | |
| Social Perceptiveness | 3.0 | |
| Time Management | 2.9 | |
| Persuasion | 2.8 |
Skills in demand
Skills employers ask for in job postings for this occupation (Lightcast), with whether each is a common or specialized skill.
Showing the top 40 of 84.
Tools & technology
Showing the top 40 of 159.
Work context
How characteristic each condition is of the job, on O*NET's 1–5 context scale (higher = more present in day-to-day work). Each condition links to how it varies across all occupations.
How to get in
- Job zone
- Zone 4 — Job Zone Four: Considerable Preparation Needed
- Education
- Most of these occupations require a four-year bachelor's degree, but some do not.
- Typical entry-level education
- Bachelor's degree · BLS, the typical path — not a requirement
- Related experience
- A considerable amount of work-related skill, knowledge, or experience is needed for these occupations. For example, an accountant must complete four years of college and work for several years in accounting to be considered qualified.
- Preparation level
- SVP (7.0 to < 8.0) — total schooling plus on-the-job experience.
What to study: Business, Management, Marketing, and Related Support Services , Computer and Information Sciences and Support Services , Engineering , Multi/Interdisciplinary Studies . Fields of study crosswalked to this occupation (NCES CIP–SOC), not a requirement.
Education of current workers
Share of people in this occupation at each level of education.
| Bachelor's Degree | 78.3% | |
| High School Diploma | 4.3% | |
| Post-Secondary Certificate | 4.3% | |
| Some College Courses | 4.3% | |
| Associate's Degree (or other 2-year degree) | 4.3% | |
| Master's Degree | 4.3% |
Interests & work styles
The interests and personal qualities O*NET associates with people who do this work.
Interest areas
| Information Technology | 6.6 | |
| Mathematics/Statistics | 3.5 | |
| Management/Administration | 2.8 | |
| Office Work | 2.5 | |
| Accounting | 2.3 | |
| Engineering | 2.2 |
Career interests (Holland / RIASEC)
| Conventional | 6.4 | |
| Investigative | 4.8 | |
| Enterprising | 3.0 | |
| Realistic | 2.9 | |
| Social | 2.0 |
Work styles
| Dependability | 5.0 | |
| Attention to Detail | 4.0 | |
| Integrity | 3.0 | |
| Intellectual Curiosity | 2.2 | |
| Cautiousness | 2.1 |
Wages & employment
U.S. · annual wages (BLS OEWS)
| 10th percentile | $81,630 |
| 25th percentile | $107,900 |
| Median (50th) | $135,980 |
| 75th percentile | $169,480 |
| 90th percentile | $209,990 |
| People employed | 64,770 |
Wages and employment are reported by BLS for the broader occupation group this specialty belongs to (SOC 15-1243), not for the specialty alone.
Industries that employ this occupation
Where these workers are employed, by number of jobs (national, BLS OEWS). Pay shown is the occupation's national median, not industry-specific.
| Industry | Workers | National median pay |
|---|---|---|
| Professional, Scientific, and Technical Services · Sector | 24,380 | $138,610 |
| Finance and Insurance · Sector | 9,580 | $138,540 |
| Information · Sector | 8,510 | $151,460 |
| Management of Companies and Enterprises · Sector | 6,710 | $134,330 |
| Administrative and Support and Waste Management and Remediation Services · Sector | 3,560 | $136,890 |
| Wholesale Trade · Sector | 2,900 | $129,820 |
| Temporary Help Services · National industry | 2,020 | $140,630 |
| Health Care and Social Assistance · Sector | 2,020 | $123,410 |
| Manufacturing · Sector | 1,900 | $129,460 |
| Direct Health and Medical Insurance Carriers · National industry | 1,660 | $132,860 |
| Educational Services · Sector | 1,480 | $108,410 |
| Engineering Services · National industry | 730 | $127,520 |
Where this work is most concentrated
Industries where this occupation is far more common than in the economy as a whole. The location quotient is how many times more concentrated it is here (a value of 5 means five times its economy-wide share).
| Industry | Concentration | Workers |
|---|---|---|
| Direct Health and Medical Insurance Carriers · National industry | 8.8× | 1,660 |
| Information · Sector | 6.97× | 8,510 |
| Management of Companies and Enterprises · Sector | 5.69× | 6,710 |
| Professional, Scientific, and Technical Services · Sector | 5.39× | 24,380 |
| Finance and Insurance · Sector | 3.66× | 9,580 |
| Temporary Help Services · National industry | 1.81× | 2,020 |
| Engineering Services · National industry | 1.5× | 730 |
| Utilities · Sector | 1.31× | 320 |
Related occupations
Part of the Digital Technology career cluster.
- Database Architects · 15-1243.00 Compare →
- Database Administrators · 15-1242.00 Compare →
- Software Developers · 15-1252.00 Compare →
- Computer Systems Analysts · 15-1211.00 Compare →
- Computer Systems Engineers/Architects · 15-1299.08 Compare →
- Software Quality Assurance Analysts and Testers · 15-1253.00 Compare →
- Data Scientists · 15-2051.00 Compare →
- Blockchain Engineers · 15-1299.07 Compare →
- Business Intelligence Analysts · 15-2051.01 Compare →
- Computer Programmers · 15-1251.00 Compare →
- Document Management Specialists · 15-1299.03 Compare →
- Network and Computer Systems Administrators · 15-1244.00 Compare →
Side-by-side comparisons place two occupations’ pay, preparation, skills, and AI exposure on the same page — same data, same scale, no forecast.
What you can do with this
Options the data surfaces for Data Warehousing Specialists — not advice or a forecast. Each is a real cross-link you can follow into the evidence.
Skills that travel
Capabilities this work builds that are used across many other occupations.
Adjacent roles
Occupations O*NET rates as related — the nearby moves on the map.
Paths in
How people typically prepare for this work.
- Bachelor's degree · typical entry level
- Job zone 4 — Job Zone Four: Considerable Preparation Needed · preparation tier
- Business, Management, Marketing, and Related Support Services · field of study
- Computer and Information Sciences and Support Services · field of study
Zoom out
See where this work sits in the bigger picture.
Write a report on thisheadline · factoids · citation
Data Warehousing Specialists show 98th-percentile AI task overlap — and about 4,000 annual U.S. openings
- Data Warehousing Specialists rank in the 98th percentile (High band) for AI task overlap across U.S. occupations — a measure of how much of the work today's AI can attempt, not how much is automated.Eloundou et al. (GPTs are GPTs) + Felten AIOE
- The occupation is projected to see about 4,000 U.S. job openings per year (2024–34), counting growth and replacement — a labor-demand projection made independently of AI.BLS Employment Projections 2024–34
- BLS projects employment to be growing fast (+8.7%) from 2024 to 2034.BLS Employment Projections 2024–34
- Median annual pay is $135,980, across about 64,770 U.S. workers.BLS OEWS (May 2024)
Copy the whole kit
Data Warehousing Specialists show 98th-percentile AI task overlap — and about 4,000 annual U.S. openings • Data Warehousing Specialists rank in the 98th percentile (High band) for AI task overlap across U.S. occupations — a measure of how much of the work today's AI can attempt, not how much is automated. (Eloundou et al. (GPTs are GPTs) + Felten AIOE) • The occupation is projected to see about 4,000 U.S. job openings per year (2024–34), counting growth and replacement — a labor-demand projection made independently of AI. (BLS Employment Projections 2024–34) • BLS projects employment to be growing fast (+8.7%) from 2024 to 2034. (BLS Employment Projections 2024–34) • Median annual pay is $135,980, across about 64,770 U.S. workers. (BLS OEWS (May 2024)) Source: Singulariki — "Data Warehousing Specialists". https://singulariki.com/roles/role-15-1243-01 Note: AI task overlap measures what today's AI can attempt, not automation, job loss, or a forecast.
AssetsShare imageMethodology & sourcesPress & newsroomThe newsroom
Every line is built only from figures this page already shows and cites. AI task overlap means what today's AI can attempt — not automation, job loss, or a forecast.
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.
- O*NET 30.3 U.S. Department of Labor / National Center for O*NET Development
- BLS Occupational Employment and Wage Statistics (OEWS) May 2024 U.S. Bureau of Labor Statistics
- BLS Employment Projections 2024–2034 U.S. Bureau of Labor Statistics
- Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27) Anthropic
- Microsoft “Working with AI” working-with-ai Microsoft Research
- “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130 OpenAI / academic
Data compiled June 2, 2026. Figures are estimates, not advice.
Cite this page
Plain
Singulariki. "Data Warehousing Specialists." 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/roles/role-15-1243-01
APA
Singulariki. (2026). Data Warehousing Specialists. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/roles/role-15-1243-01
BibTeX
@misc{singulariki-role-15-1243-01,
title = {Data Warehousing Specialists},
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/roles/role-15-1243-01}
} Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.