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 →Water/Wastewater Engineers
Occupation · SOC 17-2051.02
Design or oversee projects involving provision of potable water, disposal of wastewater and sewage, or prevention of flood-related damage. Prepare environmental documentation for water resources, regulatory program compliance, data management and analysis, and field work. Perform hydraulic modeling and pipeline design.
Also called: Consulting Engineer · County Engineer · Engineer · Project Development Engineer · Dimensional Engineer · Hydraulics Engineer · Hydrologic Modeler · Remediation Engineer · Remediation Project Engineer · Wastewater Design Engineer · Wastewater Engineer · Wastewater Process Engineer
Job family: Architecture and Engineering Occupations
Take this to your AI
A source-stamped Markdown brief of this occupation — paste it into an agent, or fetch
/roles/role-17-2051-02/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.
- About average employment outlook (+5.0% by 2034)
- 23,600 openings/yr
- High AI exposure
- Median pay $99,590/yr
- Can largely be done remotely (teleworkable)
- A reversal from 2013 — rated low automation risk then (14th), high AI task-overlap now (81st)
81st-percentile task overlap — yet about 23,600 openings a year (+5% 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 |
|---|---|---|---|
| Overall AI exposure (Felten et al.) High | 85th | 1.3 | |
| LLM task exposure, γ (OpenAI / Eloundou) High | 82nd | 0.9 | |
| AI assistant applicability (Microsoft) High | 69th | 0.2 |
OpenAI's exposure study scores tasks three ways: with a language model alone (α 0.1), with simple added tooling (β 0.5), and including AI-powered software (γ 0.9). Higher means more of the job's tasks could be done at least twice as fast — not that they will be automated away.
Most of this job's tasks can be done remotely (Dingel–Neiman), which tends to track with higher digital and AI exposure.
Historical automation estimate (2013)
A pre-LLM (2013) estimate of how automatable this job is by computerization and robotics. Shown for historical context only — it is not part of any current AI ranking.
Frey–Osborne probability 0.0 · 14th percentile among occupations · Low
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.
| Analyze and recommend chemical, biological, or other wastewater treatment methods to prepare water for industrial or domestic use. | 0.5% | |
| Design water storage tanks or other water storage facilities. | 0.4% | |
| Design domestic or industrial water or wastewater treatment plants, including advanced facilities with sequencing batch reactors (SBR), membranes, lift stations, headworks, surge overflow basins, ultraviolet disinfection systems, aerobic digesters, sludge lagoons, or control buildings. | 0.2% | |
| Design or select equipment for use in wastewater processing to ensure compliance with government standards. | 0.2% | |
| Provide technical support on water resource or treatment issues to government agencies. | 0.2% | |
| Perform mathematical modeling of underground or surface water resources, such as floodplains, ocean coastlines, streams, rivers, or wetlands. | 0.2% |
Job outlook
Independent U.S. Bureau of Labor Statistics employment projection for 2024–2034 — a labor-market forecast, not an AI-impact forecast.
| Outlook | About average · +5.0% by 2034 |
| Projected annual openings | 23,600 |
| Employment 2024 → 2034 | 368,900 → 387,500 |
“Annual openings” counts new jobs plus replacements for workers who leave the occupation, so it can be large even when growth is modest.
Where this work sits on the global GenAI gradient
The ILO's 2025 global study scores generative-AI exposure on the international ISCO-08 occupation system, not US SOC. Bridged through the published (and approximate, many-to-many) IBS O*NET-SOC ↔ ISCO-08 crosswalk, this US occupation corresponds to the international occupation below. Exposure here means how much of the work's tasks today's AI can attempt — task overlap, not automation, adoption, or jobs lost.
Water/Wastewater Engineers sits at the 57th percentile of 427
occupations on the global GenAI task-exposure gradient
— exposure eased from 2023 to 2025. Each dot is one occupation; the
ringed one is this work. Exposure is task overlap, not automation or jobs lost.
30% mean task exposure (2025)
57th percentile of 427 placed occupations
−4 pts shift 2023 → 2025
| International occupation (ISCO-08) | Task exposure (2025) | Most tasks fall in |
|---|---|---|
| Civil Engineers · 2142 | 30% | Not exposed |
Read the whole six-band gradient on the GenAI exposure gradient page. The crosswalk is approximate: a US occupation can map to several international ones, and the ILO scores describe the international occupation, not this exact US role.
Tasks
All 28 tasks O*NET lists for this occupation, ordered by importance. Each links to its own page with AI-exposure and observed-use detail.
- Provide technical direction or supervision to junior engineers, engineering or computer-aided design (CAD) technicians, or other technical personnel. Core · importance 4.7
- Review and critique proposals, plans, or designs related to water or wastewater treatment systems. Core · importance 4.3
- Design domestic or industrial water or wastewater treatment plants, including advanced facilities with sequencing batch reactors (SBR), membranes, lift stations, headworks, surge overflow basins, ultraviolet disinfection systems, aerobic digesters, sludge lagoons, or control buildings. Core · importance 4.2
- Evaluate the operation and maintenance of water or wastewater systems to identify ways to improve their efficiency. Core · importance 4.0
- Design or select equipment for use in wastewater processing to ensure compliance with government standards. Core · importance 4.0
- Design pumping systems, pumping stations, pipelines, force mains, or sewers for the collection of wastewater. Core · importance 4.0
- Design water distribution systems for potable or non-potable water. Core · importance 4.0
- Conduct water quality studies to identify and characterize water pollutant sources. Core · importance 3.9
- Analyze and recommend chemical, biological, or other wastewater treatment methods to prepare water for industrial or domestic use. Core · importance 3.9
- Identify design alternatives for the development of new water resources. Core · importance 3.8
- Design water runoff collection networks, water supply channels, or water supply system networks. Core · importance 3.8
- Design water or wastewater lift stations, including water wells. Core · importance 3.8
- Conduct cost-benefit analyses for the construction of water supply systems, runoff collection networks, water and wastewater treatment plants, or wastewater collection systems. Core · importance 3.8
- Analyze storm water or floodplain drainage systems to control erosion, stabilize river banks, repair channel streams, or design bridges. Core · importance 3.7
- Conduct feasibility studies for the construction of facilities, such as water supply systems, runoff collection networks, water and wastewater treatment plants, or wastewater collection systems. Core · importance 3.7
- Provide technical support on water resource or treatment issues to government agencies. Core · importance 3.7
- Oversee the construction of decentralized or on-site wastewater treatment systems, including reclaimed water facilities. Core · importance 3.6
- Develop plans for new water resources or water efficiency programs. Core · importance 3.6
- Perform hydrological analyses, using three-dimensional simulation software, to model the movement of water or forecast the dispersion of chemical pollutants in the water supply. Core · importance 3.6
- Perform hydraulic analyses of water supply systems or water distribution networks to model flow characteristics, test for pressure losses, or to identify opportunities to mitigate risks and improve operational efficiency. Core · importance 3.6
- Write technical reports or publications related to water resources development or water use efficiency. Core · importance 3.6
- Analyze and recommend sludge treatment or disposal methods. Core · importance 3.5
- Design water storage tanks or other water storage facilities. Core · importance 3.5
- Design sludge treatment plants. Core · importance 3.5
- Gather and analyze water use data to forecast water demand. Core · importance 3.4
- Conduct environmental impact studies related to water and wastewater collection, treatment, or distribution. Core · importance 3.4
- Perform mathematical modeling of underground or surface water resources, such as floodplains, ocean coastlines, streams, rivers, or wetlands. Supplemental · importance 3.4
- Analyze the efficiency of water delivery structures, such as dams, tainter gates, canals, pipes, penstocks, or cofferdams. Core · importance 3.3
Work activities
- Prepare technical or operational reports.
- Evaluate designs or specifications to ensure quality.
- Advise others regarding green practices or environmental concerns.
- Supervise engineering or other technical personnel.
- Provide technical guidance to other personnel.
- Recommend technical design or process changes to improve efficiency, quality, or performance.
- Develop technical methods or processes.
- Prepare detailed work plans.
- Select tools, equipment, or technologies for use in operations or projects.
- Design civil structures or systems.
- Investigate the environmental impact of projects.
- Create models of engineering designs or methods.
- Analyze operational data to evaluate operations, processes or products.
- Direct environmental development activities.
- Research advanced engineering designs or applications.
- Analyze costs and benefits of proposed designs or projects.
- Analyze physical, survey, or geographic data.
- Design structures or facilities.
- Design industrial processing systems.
- Identify opportunities to improve operational efficiency.
- Evaluate characteristics of equipment or systems.
Knowledge, skills & abilities
O*NET importance rating, from 1 (not important) to 5 (extremely important).
Knowledge
| Engineering and Technology | 4.7 | |
| Design | 4.5 | |
| English Language | 4.2 | |
| Mathematics | 4.2 | |
| Building and Construction | 3.8 | |
| Administration and Management | 3.6 | |
| Mechanical | 3.5 | |
| Physics | 3.5 | |
| Chemistry | 3.5 | |
| Customer and Personal Service | 3.4 | |
| Law and Government | 3.3 |
Essential skills
| Reading Comprehension | 4.0 | |
| Writing | 4.0 | |
| Critical Thinking | 4.0 | |
| Active Listening | 3.9 | |
| Mathematics | 3.9 | |
| Speaking | 3.8 | |
| Monitoring | 3.6 | |
| Science | 3.5 |
Transferable skills
| Judgment and Decision Making | 4.0 | |
| Complex Problem Solving | 3.9 | |
| Systems Analysis | 3.9 | |
| Systems Evaluation | 3.9 | |
| Time Management | 3.8 |
Abilities
| Oral Comprehension | 4.0 | |
| Written Comprehension | 4.0 | |
| Oral Expression | 4.0 | |
| Written Expression | 4.0 | |
| Deductive Reasoning | 4.0 | |
| Inductive Reasoning | 4.0 | |
| Information Ordering | 4.0 | |
| Fluency of Ideas | 3.9 | |
| Problem Sensitivity | 3.9 | |
| Mathematical Reasoning | 3.9 | |
| Category Flexibility | 3.8 | |
| Number Facility | 3.8 | |
| Visualization | 3.8 | |
| Near Vision | 3.8 | |
| Originality | 3.6 | |
| Speech Clarity | 3.4 |
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 44.
Tools & technology
Showing the top 40 of 50.
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: Engineering . 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 | 69.6% | |
| Master's Degree | 26.1% | |
| First Professional Degree | 4.3% |
Interests & work styles
The interests and personal qualities O*NET associates with people who do this work.
Career interests (Holland / RIASEC)
| Realistic | 5.6 | |
| Investigative | 5.3 | |
| Conventional | 4.5 | |
| Enterprising | 2.9 | |
| Artistic | 1.9 | |
| Social | 1.8 |
Wages & employment
U.S. · annual wages (BLS OEWS)
| 10th percentile | $65,920 |
| 25th percentile | $78,790 |
| Median (50th) | $99,590 |
| 75th percentile | $128,290 |
| 90th percentile | $160,990 |
| People employed | 355,410 |
Wages and employment are reported by BLS for the broader occupation group this specialty belongs to (SOC 17-2051), 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 | 202,800 | $99,670 |
| Engineering Services · National industry | 188,160 | $99,380 |
| Construction · Sector | 44,580 | $82,970 |
| Administrative and Support and Waste Management and Remediation Services · Sector | 5,010 | $108,140 |
| Manufacturing · Sector | 4,190 | $104,310 |
| Management of Companies and Enterprises · Sector | 3,180 | $117,740 |
| Real Estate and Rental and Leasing · Sector | 2,500 | $90,510 |
| Educational Services · Sector | 2,070 | $102,000 |
| Plumbing, Heating, and Air-Conditioning Contractors · National industry | 2,050 | $89,610 |
| Temporary Help Services · National industry | 2,050 | $129,690 |
| Utilities · Sector | 1,940 | $113,380 |
| Wholesale Trade · Sector | 1,910 | $81,490 |
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 |
|---|---|---|
| Engineering Services · National industry | 70.6× | 188,160 |
| Professional, Scientific, and Technical Services · Sector | 8.17× | 202,800 |
| Testing Laboratories and Services · National industry | 2.65× | 1,040 |
| Construction · Sector | 2.38× | 44,580 |
| Fossil Fuel Electric Power Generation · National industry | 1.95× | 320 |
| Power and Communication Line and Related Structures Construction · National industry | 1.78× | 960 |
| Poured Concrete Foundation and Structure Contractors · National industry | 1.53× | 910 |
| Utilities · Sector | 1.45× | 1,940 |
Related occupations
Part of the Construction and Public Service & Safety career clusters.
- Water Resource Specialists · 11-9121.02 Compare →
- Environmental Engineers · 17-2081.00 Compare →
- Civil Engineers · 17-2051.00 Compare →
- Brownfield Redevelopment Specialists and Site Managers · 11-9199.11 Compare →
- Petroleum Engineers · 17-2171.00 Compare →
- Energy Engineers, Except Wind and Solar · 17-2199.03 Compare →
- Environmental Science and Protection Technicians, Including Health · 19-4042.00 Compare →
- Chemical Engineers · 17-2041.00 Compare →
- Wind Energy Engineers · 17-2199.10 Compare →
- Transportation Engineers · 17-2051.01 Compare →
- Water and Wastewater Treatment Plant and System Operators · 51-8031.00 Compare →
- Hydrologic Technicians · 19-4044.00 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 Water/Wastewater Engineers — 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
- Engineering · field of study
Zoom out
On the global GenAI exposure gradient this work sits around the 57th percentile of 427 international occupations.
Write a report on thisheadline · factoids · citation
Water/Wastewater Engineers show 81st-percentile AI task overlap — and about 23,600 annual U.S. openings
- Water/Wastewater Engineers rank in the 81st 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 23,600 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 about average (+5%) from 2024 to 2034.BLS Employment Projections 2024–34
- Median annual pay is $99,590, across about 355,410 U.S. workers.BLS OEWS (May 2024)
Copy the whole kit
Water/Wastewater Engineers show 81st-percentile AI task overlap — and about 23,600 annual U.S. openings • Water/Wastewater Engineers rank in the 81st 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 23,600 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 about average (+5%) from 2024 to 2034. (BLS Employment Projections 2024–34) • Median annual pay is $99,590, across about 355,410 U.S. workers. (BLS OEWS (May 2024)) Source: Singulariki — "Water/Wastewater Engineers". https://singulariki.com/roles/role-17-2051-02 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
- AI Occupational Exposure (AIOE) Felten, Raj & Seamans academic
- ILO / Gmyrek et al. GenAI exposure gradient 2025 International Labour Organization
- IBS O*NET-SOC ↔ ISCO-08 occupation crosswalk 2022 Institute for Structural Research (IBS)
- Frey & Osborne (2013) frey-osborne-automation academic
- Dingel & Neiman (2020) dingel-neiman-workathome academic
Data compiled June 2, 2026. Figures are estimates, not advice.
Cite this page
Plain
Singulariki. "Water/Wastewater Engineers." 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; AI Occupational Exposure (AIOE) Felten, Raj & Seamans; ILO / Gmyrek et al. GenAI exposure gradient 2025; IBS O*NET-SOC ↔ ISCO-08 occupation crosswalk 2022; Frey & Osborne (2013) frey-osborne-automation; Dingel & Neiman (2020) dingel-neiman-workathome. Accessed June 7, 2026. https://singulariki.com/roles/role-17-2051-02
APA
Singulariki. (2026). Water/Wastewater Engineers. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/roles/role-17-2051-02
BibTeX
@misc{singulariki-role-17-2051-02,
title = {Water/Wastewater Engineers},
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; AI Occupational Exposure (AIOE) Felten, Raj & Seamans; ILO / Gmyrek et al. GenAI exposure gradient 2025; IBS O*NET-SOC ↔ ISCO-08 occupation crosswalk 2022; Frey & Osborne (2013) frey-osborne-automation; Dingel & Neiman (2020) dingel-neiman-workathome. Accessed June 7, 2026},
url = {https://singulariki.com/roles/role-17-2051-02}
} Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.