# Water/Wastewater Engineers

> 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.

- **SOC code:** 17-2051.02
- **Canonical URL:** https://singulariki.com/roles/role-17-2051-02
- **Also known as:** Consulting Engineer, County Engineer, Engineer, Project Development Engineer, Dimensional Engineer, Hydraulics Engineer, Hydrologic Modeler, Remediation Engineer
- **Frame:** "AI exposure" means task overlap (how codifiable the work is), not jobs lost or a forecast. Every figure below is traced to a named public dataset.

## What this work is

**Core tasks** (O*NET):
- Provide technical direction or supervision to junior engineers, engineering or computer-aided design (CAD) technicians, or other technical personnel.
- Review and critique proposals, plans, or designs related to water or wastewater treatment systems.
- 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.
- Evaluate the operation and maintenance of water or wastewater systems to identify ways to improve their efficiency.
- Design or select equipment for use in wastewater processing to ensure compliance with government standards.
- Design water distribution systems for potable or non-potable water.
- Design pumping systems, pumping stations, pipelines, force mains, or sewers for the collection of wastewater.
- Conduct water quality studies to identify and characterize water pollutant sources.
- Analyze and recommend chemical, biological, or other wastewater treatment methods to prepare water for industrial or domestic use.
- Identify design alternatives for the development of new water resources.
- Design water runoff collection networks, water supply channels, or water supply system networks.
- Design water or wastewater lift stations, including water wells.

## Skills, tools, capabilities

**Knowledge, skills & abilities** (O*NET, highest importance first):
- Engineering and Technology _(knowledge)_
- Design _(knowledge)_
- English Language _(knowledge)_
- Mathematics _(knowledge)_
- Reading Comprehension _(essential_skill)_
- Writing _(essential_skill)_
- Critical Thinking _(essential_skill)_
- Judgment and Decision Making _(transferable_skill)_
- Oral Comprehension _(ability)_
- Written Comprehension _(ability)_
- Oral Expression _(ability)_
- Written Expression _(ability)_

**Skills in demand:**
- English Language _(Common Skill)_
- Mathematics _(Common Skill)_
- Writing _(Common Skill)_
- Reading Comprehension _(Common Skill)_
- Information Ordering _(Specialized Skill)_
- Inductive Reasoning _(Common Skill)_
- Deductive Reasoning _(Common Skill)_
- Critical Thinking _(Common Skill)_
- Systems Analysis _(Specialized Skill)_
- Complex Problem Solving _(Common Skill)_
- Active Listening _(Common Skill)_
- Visualization _(Specialized Skill)_

**Tools & technology:**
- Autodesk AutoCAD _(hot technology, in demand)_
- Autodesk AutoCAD Civil 3D _(hot technology, in demand)_
- Autodesk Revit _(hot technology, in demand)_
- Bentley MicroStation _(hot technology, in demand)_
- ESRI ArcGIS software _(hot technology, in demand)_
- Microsoft Excel _(hot technology, in demand)_
- Microsoft Office software _(hot technology, in demand)_
- Microsoft PowerPoint _(hot technology, in demand)_
- Bash _(hot technology)_
- Microsoft Access _(hot technology)_
- Microsoft Outlook _(hot technology)_
- Microsoft Project _(hot technology)_

## AI exposure & outlook

- **AI task-overlap index:** 81st percentile (High) across all occupations — composite of current-era exposure studies (ai-exposure-index-v1).
- **Overall AI exposure (Felten et al.):** 85th percentile (High) — source: felten_aioe.
- **LLM task exposure, γ (OpenAI / Eloundou):** 82nd percentile (High) — source: eloundou_gamma.
- **AI assistant applicability (Microsoft):** 69th percentile (High) — source: microsoft_applicability.
- **Frey–Osborne (2013, historical computerization estimate):** 14th percentile — kept separate from current-era studies.
- **Remote-capable (Dingel–Neiman):** yes — task structure, not who actually works remote.
- **Projected employment (BLS 2024–34):** 5.0% growth (About average); 23.6k annual openings; 368.9k → 387.5k jobs.
- **Pay & employment (BLS OEWS, May 2024):** median $99,590; 355,410 employed.

## Sources

- **O*NET** (30.3) — U.S. Department of Labor / National Center for O*NET Development. https://www.onetcenter.org/database.html
- **BLS Occupational Employment and Wage Statistics (OEWS)** (May 2024) — U.S. Bureau of Labor Statistics. https://www.bls.gov/oes/
- **BLS Employment Projections** (2024–2034) — U.S. Bureau of Labor Statistics. https://www.bls.gov/emp/
- **Anthropic Economic Index** (v4 (2026-01-15) + v2 (2025-03-27)) — Anthropic. https://www.anthropic.com/economic-index
- **Microsoft “Working with AI”** (working-with-ai) — Microsoft Research. https://www.microsoft.com/en-us/research/
- **“GPTs are GPTs” (Eloundou et al.)** (arXiv 2303.10130) — OpenAI / academic. https://arxiv.org/abs/2303.10130
- **AI Occupational Exposure (AIOE)** (Felten, Raj & Seamans) — academic. https://github.com/AIOE-Data/AIOE
- **Frey & Osborne (2013)** (frey-osborne-automation) — academic. https://www.oxfordmartin.ox.ac.uk/publications/the-future-of-employment/
- **Dingel & Neiman (2020)** (dingel-neiman-workathome) — academic. https://github.com/jdingel/DingelNeiman-workathome

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_Generated from Singulariki's joined dataset; data snapshot 2026-06-02T21:00:32.945303+00:00. https://singulariki.com/roles/role-17-2051-02_