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Key statistics

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

3 of 8

Track

Individual contributor

Family rungs priced

P1 · P2 · P3 · P4 · P5 · P6

49-0000

manufacturing

Coordinates

3 / 4 spaces

pay@2 · 2026-07

What this role is

Applies protective coatings to manufactured parts and equipment while sourcing appropriate materials for each job. At the Mid-Level Professional (P3) level, the role owns features or a sub-system end-to-end, adapts existing approaches, and drives project / team outcomes. Mentors juniors informally.

What this level does

Independently own maintenance and repair across a diverse set of production equipment of moderate-to-high complexity, planning day-to-day work against production priorities
Identify and implement improvements to machinery, equipment reliability, efficiency, and maintenance procedures by evaluating recurring failure patterns
Analyze CMMS fault history and equipment data to convert reactive break-fix work into scheduled preventive tasks for assigned lines
Coordinate the activities of a small maintenance crew or contractors on planned shutdown and changeover work
Serve as escalation point for complex faults that developing technicians cannot resolve, and network with equipment vendors on spares and specs

Knowledge applied: Applies broad cross-trade maintenance knowledge and CMMS data analysis to a diverse asset base, converting reactive work into scheduled prevention.
Complexity & problem solving: Evaluates identifiable failure factors across varied equipment; plans own work against production priorities with milestone review.
Collaboration & interaction: Networks with equipment vendors and senior maintenance staff; may coordinate a small crew or contractors on planned work.
Typical experience: 5+ years of maintenance experience with demonstrated independent troubleshooting across equipment types.

Skills at this level

Electrical fundamentals: — Reads electrical circuits and applies basic electricity knowledge to install, inspect, and repair the electrical elements of industrial production machinery.
CMMS work-order execution: — Uses a Computerized Maintenance Management System to receive, record, and close maintenance work orders and to log fault history, parts usage, and PM completion.
Preventive maintenance execution: — Follows manufacturer procedures to carry out scheduled inspection and servicing of production equipment and building systems to keep machines operational and prevent breakdowns.
Mechanical trade proficiency: — Performs maintenance and repair of moderate-to-high-complexity production equipment with hands-on competence in at least one building trade.
Fault diagnosis and troubleshooting: — Isolates the root cause of mechanical and electrical equipment failures on the floor and selects the correct tools and parts to restore production.
Maintenance improvement and procedure development: — Identifies and implements improvements to machinery, equipment reliability, efficiency, and the maintenance procedures themselves based on recurring failure patterns.
Reliability-Centered Maintenance (RCM): — Develops maintenance strategies that prioritize tasks by equipment criticality and failure consequence to improve overall plant reliability and safety.
Failure analysis: — Investigates high-impact equipment failures using fatigue, wear, and load-case reasoning to specify durable engineering fixes instead of repeated repair.
Predictive maintenance and data analysis: — Analyzes datasets from IoT sensors and applies machine-learning models to anticipate equipment failures before they cause unplanned downtime.
Commissioning and installation strategy: — Writes installation and commissioning guidelines and maintenance strategies for new or modified equipment entering the production environment.
Maintenance stores and spares control: — Establishes criticality-based spare-parts inventory and stores control so that failure-critical components are available without over-stocking.
Autonomous Maintenance deployment: — Implements operator-driven Autonomous Maintenance routines across facilities so production teams perform basic cleaning, inspection, and lubrication.
Multi-site reliability program leadership: — Standardizes maintenance and predictive-maintenance programs across multiple manufacturing sites while meeting production, safety, and cost targets.
Capital project support: — Scopes and supports execution of capital projects for equipment replacement and technology upgrades, balancing lifecycle cost, uptime, and reliability risk.

Model-authored from 21 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

Maintenance — median with , by . Real canon data.

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

+7.9%Maintenance and Repair Workers, General · United States

1,418,990 → 1,531,700 jobs

159,800 openings / year, split into:

replacement / exits 153,607

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: +3.8%
Growth share of hiring: 4%
Exit / retention pressure high: 96%
Openings / year: 159,800

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 P3 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$142k

San Francisco-Oakland-Fremont, CA$127k

Washington-Arlington-Alexandria, DC-VA-MD-WV$118k

Boulder, CO$116k

Seattle-Tacoma-Bellevue, WA$116k

Boston-Cambridge-Newton, MA-NH$111k

Lexington Park, MD$108k

Trenton-Princeton, NJ$108k

Pay only — metro-level demand isn't in public data (it needs job postings). National median $85k; 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 P3 (P3 — Mid-Level Professional) from the levels around it — this level only. Every word is real canon for this profile.

Scope: Features or a sub-system end-to-end
Autonomy: Works independently on standard work; reviewed on the non-standard
Complexity: Diverse problems; adapts existing approaches
Impact: Project / team outcomes
Decision rights: Owns implementation decisions for own scope
Leadership: Mentors juniors informally

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

Promotion

The next rung from P3 is P4.

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 Maintenance Officer	jf_maintenance::E3	$363,257	confident0.06
Maintenance Coatings Manager	jf_maintenance::M3	$124,177	confident0.06
Senior Protective Coatings Technician	jf_maintenance::S3	$51,142	confident0.06
Coatings Engineer	jf_maintenance::P2	$74,658	confident0.06

Capability cluster

O*NET 49-9071

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

P3

jf_maintenance::P3

Protective Coatings Technician

Maintenance

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: P
Superfunction: manufacturing
Function: manufacturing_expansion
Family: maintenance
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").

Chemistry, Manufacturing & Controls (CMC) · P3review0.17

Lean Manufacturing · P3review0.17

Machine Shop · P3review0.17

Manufacturing Engineering · P3review0.17

Pilot Plant Operations · P3review0.17

Production Test · P3review0.17

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 49-9071	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)