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Key statistics

The identity block — every fact is canon, none is generated.

3 of 8

Track

Management

Family rungs priced

M1 · M2 · M3 · M4 · M5 · M6

49-0000

industrial_energy_operations

Coordinates

3 / 4 spaces

pay@2 · 2026-07

What this role is

Manages the team and operations responsible for maintaining engine rooms and plant equipment to ensure safe, reliable facility performance. At the Senior Manager (M3) level, the role owns multiple teams or a sub-function, multi-team execution and resourcing trade-offs, and drives sub-function outcomes. Manages managers and/or several teams.

What this level does

Lead and direct the plant's preventive and corrective maintenance activities across multiple crews to ensure efficient, reliable operations
Establish effective maintenance procedures including planning, scheduling, material support, and analysis of cost and performance
Manage the maintenance department's operational spend and staffing, evaluating recurring equipment failure trends to prioritize corrective work
Analyze production equipment to prevent costs from unexpected downtime and identify improvement opportunities across the unit
Ensure maintenance activities comply with mechanical integrity and preventive maintenance programs, participating in safety incident investigations

Knowledge applied: Applies maintenance planning, scheduling, cost/performance analysis, and mechanical-integrity program knowledge to run a maintenance department.
Complexity & problem solving: Addresses diverse maintenance issues; evaluates equipment failure and downtime trends to prioritize corrective and preventive work.
Collaboration & interaction: Leads maintenance crews and interfaces with production leadership and material/supply functions on maintenance support.
Typical experience: 5–7+ years managing maintenance professionals and departmental budgets.

Skills at this level

Maintenance Planning and Scheduling: — Establishes maintenance procedures covering planning, scheduling, material support, and analysis of cost and performance to keep plant equipment running efficiently and minimize downtime.
Preventive and Corrective Maintenance Leadership: — Directs the plant's preventive and corrective maintenance activities across power distribution, HVAC, and production equipment, coordinating routine servicing with breakdown repair to sustain uptime.
Reliability and Uptime Analytics: — Leads data-mining efforts to establish reliability and uptime metrics, analyzing production equipment to prevent unexpected downtime costs and identify improvement opportunities.
Mechanical, Electrical and Hydraulic Troubleshooting: — Diagnoses and resolves electrical, mechanical, and hydraulic malfunctions on plant machinery and extraction/energy equipment such as turbines, guiding crews through repair while observing safety precautions.
Maintenance Budget and Capital Project Management: — Holds responsibility for the yearly maintenance budget and manages capital project planning and implementation for equipment replacement, plant improvements, and expansions.
Mechanical Integrity and Safety Compliance: — Ensures maintenance activities comply with mechanical integrity and preventive maintenance programs and leads safety incident investigations to identify root cause and prevent recurrence.
CMMS Maintenance Management: — Uses a Computerized Maintenance Management System to log trouble calls, track preventive maintenance completion, and record equipment fault history so maintenance and operator records stay accurate.
Operations Monitoring: — Watches gauges, dials, and indicators across plant equipment to confirm machines are functioning properly and to trigger maintenance intervention before failure.
Maintenance Team Leadership and Development: — Supervises and develops crews of maintenance technicians and mechanics, assigning work, coaching on procedures, and building the multi-disciplinary trade competency needed for energy/mining assets.
Multi-Site Asset Strategy: — Sets long-term maintenance and reliability strategy across multiple, often remote energy/mining sites, accounting for asset mobility and coordinating standards and capital programs across facilities.
Process Improvement and Root Cause Analysis: — Applies problem solving and process improvement to recurring equipment failures, identifying root causes and driving corrective/preventive actions that reduce downtime and cost.

Model-authored from 24 retrieved sources, then adversarially reviewed by an independent judge panel and held to a minimum-evidence floor before publication. Distinct from corpus-extracted content, which is labelled as such.

Pay across the ladder

Plant Maintenance (Energy/Mining) — median with , by . Real canon data.

National-base pricing — this family's function differential is pending review, so dollar levels are not function-adjusted (level-over-level % is unaffected).

Pay figures are modeled estimates from our market equation — level-differentiated, with honest-wide bands. They refresh as new leveling evidence lands; treat per-role dollars as directional.

Demand — is the field growing, or just turning over?

SOC 49-0000 · national

Employment growth 2019–2024, BLS OEWSobserved

+23.7%First-Line Supervisors of Mechanics, Installers, and Repairers · United States

485,700 → 600,680 jobs

52,400 openings / year, split into:

replacement / exits 50,486

Growth — new jobs (4%)Exits — backfill (96%)

4% of hiring here is genuine expansion; the rest backfills people who move on.

Projected growth 2024–34 expanding: +3.1%
Growth share of hiring: 4%
Exit / retention pressure high: 96%
Openings / year: 52,400

Two quantities, kept apart: observed = employment growth differenced from two BLS OEWS vintages (what already happened); projected = BLS Employment Projections 2024–34, openings decomposed into growth + exits (growth derived from projected employment change). Neither is a pay figure.

Where this role sits — growth vs. pay

level M3 held

Demand axis is projected growth (not raw openings — that just measures churn). A curated, de-duplicated set of recognizable occupations held at this level; this role is highlighted.

Where it pays — by metro

OEWS metro median

San Jose-Sunnyvale-Santa Clara, CA$207k

San Francisco-Oakland-Fremont, CA$186k

Washington-Arlington-Alexandria, DC-VA-MD-WV$172k

Boulder, CO$169k

Seattle-Tacoma-Bellevue, WA$169k

Boston-Cambridge-Newton, MA-NH$162k

Lexington Park, MD$158k

Trenton-Princeton, NJ$157k

Pay only — metro-level demand isn't in public data (it needs job postings). National median $124k; the demand-cube initiative will add growth-by-metro.

What changes across the ladder

Level-distinction canon isn't available for the adjacent levels of this profile yet.

Level differentiators

What separates M3 (M3 — Senior Manager) from the levels around it — this level only. Every word is real canon for this profile.

Scope: Multiple teams or a sub-function
Autonomy: Sets goals within functional strategy
Complexity: Multi-team execution and resourcing trade-offs
Impact: Sub-function outcomes
Decision rights: Owns goals, budget input, and people decisions across teams
Leadership: Manages managers and/or several teams

Full level-by-level matrix (side by side across the ladder) lives on the Ladder drill-down — not here.

Promotion

The next rung from M3 is M4.

Performance criteria for this profile render in the assessment kit →

People also watch

Nearest coordinate neighbors — same , same level. Each row's (confident / review / no match) comes from its — computed, not curated.

Profile	Key	Median	Δ structural
Chief Plant Maintenance Officer	jf_plant_maintenance_energy_mining::E3	$352,063†	confident0.06
Plant Maintenance Engineer	jf_plant_maintenance_energy_mining::P3	$82,468†	confident0.06
Senior Plant Maintenance Technician	jf_plant_maintenance_energy_mining::S3	$49,566†	confident0.06
Senior Plant Maintenance Supervisor	jf_plant_maintenance_energy_mining::M2	$110,455†	confident0.06

†National-base pricing — this family's function differential is pending review, so the dollar level is not function-adjusted.

Capability cluster

O*NET 49-1011

Core to this role. Click any element with an ⓘ for its O*NET definition. A job-specific capability model (SkillFrame) will sharpen this and add worked examples.

The Job Swatch

M3

jf_plant_maintenance_energy_mining::M3

Plant Maintenance Manager

Plant Maintenance (Energy/Mining)

The swatch is JobFrame's core primitive: a hueset deterministically by the role's superfunction, the profileKey as its color code, the level ladder, and a content fingerprint. Two swatches that look alike are alike.

Because every role carries computable coordinates, similarity, leveling, and pricing become measurable instead of arguable— the whole point of "Pantone for jobs."

Structural

structural@1

Where it sits— position in the work taxonomy + level (weighted Gower, level > function > focus).

Track: M
Superfunction: industrial_energy_operations
Function: plant_operations
Family: plant_maintenance_energy_mining
Universal level: 3 / 8

Content

content@2

What it's about— a fingerprint over the role's tasks & capabilities.

Two roles can sit far apart structurally yet be close in content — that gap is itself a signal.

3-state matching

How any two swatches compare — a real distance in coordinate space, resolved to a calibrated verdict (never a fake "94% match").

Mining Processing Plant · M3review0.17

Nuclear Power Plant · M3review0.17

Plant Operations (Energy/Mining) · M3review0.17

Power Plant Management · M3review0.17

Refinery · M3review0.17

Renewables Plant · M3review0.17

Editions — frozen & versioned

structural@1live

Released 2026-06-17

content@2live

Released 2026-07-28

pay@2live

Released 2026-07-02

semantic@1live

Released 2026-07-02

Coordinates belong to a frozen, versioned edition — a coordinate computed today still means the same thing next quarter. Re-fitting issues a new edition, so comparisons are never silently redefined.

How to read this profile

Every number here is traceable — to a named source, a stated method, and an as-of date — and each value is labeled by how we know it: observed from data, computed by a model, projected forward, or governed canon. Nothing is a black box, and nothing is invented to fill a gap.

Where every number comes from

What	Source & method	Edition	State
Median pay + range	JobFrame pay equation (function base × family multiplier × level × focus differential)	pay@2	computed
Pay across the ladder	Same equation applied at each universal level	pay@2	computed
Demand — growth & openings	BLS Employment Projections; openings decomposed into growth + exits	EP 2024–34	projected
Pay by metro	BLS OEWS metropolitan medians	OEWS 2024	observed
Level distinctions	JobFrame universal-level canon (scope · autonomy · complexity · impact · decision rights · leadership)	canon	canon
Capability cluster	O*NET Knowledge / Skills / Abilities	O*NET 49-1011	computed
Coordinates	JobFrame coordinate system — structural (weighted Gower) + content fingerprint	structural@1 · content@2 · pay@2 · semantic@1	computed
Related roles	Nearest neighbors in the structural coordinate space	structural@1	computed

The principles behind the numbers

Ranges, not false precision

Pay is P10 · median · P90, never a single misleading number.

Three honest states, never a fake %

Role matches resolve to confident / review / no-match — a calibrated verdict, not a made-up percentage.

Provenance on every value

Each number carries whether it's observed, computed, projected, or canon — so you always know how much to lean on it.

Gaps shown as gaps

When a figure isn't available at the grain you need, we say so — we don't fabricate a number to fill the cell.

Frozen, versioned editions

Pay and coordinate editions are pinned, so a comparison you make today still means the same thing next quarter.

Privacy by min-N

Any aggregate over people is suppressed below a minimum count, so no individual is identifiable.

Freshness

As of2026-07-30Editioncanon-v2@2.1.0-completeSourcecanon-v2 cell + salary-benchmark (model)