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Key statistics

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

2 of 8

Track

Executive

Family rungs priced

E1 · E2 · E3 · E4 · E5

49-0000

manufacturing

Coordinates

3 / 4 spaces

pay@2 · 2026-07

What this role is

Executive leader responsible for the enterprise-wide strategy, sourcing, and execution of maintenance and protective coatings programs across all manufacturing facilities. At the Senior Director (Executive) (E2) level, the role owns multiple functions or a major area, multi-function strategy and risk, and drives major-area outcomes. Leads function leaders.

What this level does

Lead maintenance, reliability, and equipment-engineering across multiple manufacturing sites through site VPs/Directors, ensuring optimal equipment performance and consistent reliability standards network-wide
Direct cross-functional decisions where maintenance strategy intersects production, capital, and safety — where a wrong asset-reliability call could impact multi-site output and business viability
Standardize predictive maintenance and reliability-centered programs, maintenance stores control, and Autonomous Maintenance across divisions, reconciling site-specific facility and equipment constraints into one operating model
Negotiate major maintenance service contracts, spares strategies, and capital-equipment commitments with OEM partners and top internal leaders across the division
Own the multi-site maintenance-reporting and KPI framework, consolidating downtime, reliability, and maintenance-cost data into division-level performance targets

Knowledge applied: Applies cross-functional command of maintenance strategy across sites, integrating reliability engineering with production, capital, and safety to build one multi-site maintenance operating model.
Complexity & problem solving: Addresses abstract, high-consequence trade-offs — spares strategy, standardization vs. site autonomy, capital timing — where reliability decisions may impact multi-site output and business viability.
Collaboration & interaction: Negotiates major service/capital-equipment contracts and reconciles priorities with top internal leaders; leads multiple sites/divisions through VPs and Directors (E1–E2).
Typical experience: 15+ years, including strategic leadership of maintenance/reliability across multiple manufacturing units.

Skills at this level

Equipment maintenance: — Directs preventive/routine and corrective maintenance of production equipment — conveyors, hydraulic lifts, HVAC, electrical and plumbing systems — to keep small technical faults from escalating into line-stopping failures.
Predictive maintenance techniques: — Deploys vibration analysis, infrared thermography, ultrasonic testing, and oil analysis to detect impending equipment failure and convert reactive downtime into scheduled intervention across the asset base.
Reliability-centered maintenance: — Establishes standardized maintenance programs, maintenance stores control, and Autonomous Maintenance so equipment reliability is engineered and governed rather than restored after breakdown.
Lean manufacturing: — Applies continuous-improvement techniques to maintenance and reliability work, removing waste from maintenance cycles and driving asset availability against uptime and cost targets.
Process improvement: — Redesigns maintenance and reliability workflows — from work-order flow to shift handoff and stores replenishment — to raise equipment performance and lower total maintenance cost.
Capital project execution: — Supports and prioritizes capital projects for plant equipment and facility modernization, weighing reliability gains, total cost of ownership, and production continuity in investment decisions.
SCADA and PLC monitoring: — Governs supervisory control and data acquisition (SCADA) and programmable logic controller (PLC) systems as the enterprise instrumentation layer for monitoring equipment condition and triggering reliability action.
Maintenance-management systems (SAP/ERP): — Uses SAP/ERP work-order, asset, and stores data to consolidate downtime, reliability, and maintenance-cost metrics into division- and enterprise-level performance reporting.
Energy management (DDC): — Applies digital direct-control (DDC) energy-management systems to facility maintenance so building and utility systems are run for reliability and energy efficiency across sites.
Maintenance reporting and KPI governance: — Consolidates routine maintenance reports and safety-check records into a KPI framework that tracks downtime, reliability, and cost as executive operating targets.
Team leadership under pressure: — Leads, guides, and inspires maintenance and reliability teams through equipment obstacles and high-pressure downtime situations, mentoring engineers and setting technical standards.

Model-authored from 19 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

+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 E2 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$555k

San Francisco-Oakland-Fremont, CA$498k

Washington-Arlington-Alexandria, DC-VA-MD-WV$460k

Boulder, CO$454k

Seattle-Tacoma-Bellevue, WA$454k

Boston-Cambridge-Newton, MA-NH$435k

Lexington Park, MD$424k

Trenton-Princeton, NJ$421k

Pay only — metro-level demand isn't in public data (it needs job postings). National median $333k; 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 E2 (E2 — Senior Director (Executive)) from the levels around it — this level only. Every word is real canon for this profile.

Scope: Multiple functions or a major area
Autonomy: Owns area-level strategy
Complexity: Multi-function strategy and risk
Impact: Major-area outcomes
Decision rights: Owns strategy and resourcing across functions
Leadership: Leads function leaders

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

Promotion

The next rung from E2 is E3.

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
Senior Supervisor, Maintenance & Coating Operations	jf_maintenance::M2	$113,967	confident0.06
Coatings Engineer	jf_maintenance::P2	$74,658	confident0.06
Protective Coatings Technician	jf_maintenance::S2	$44,288	confident0.06
VP of Maintenance	jf_maintenance::E1	$174,847	confident0.06

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

E2

jf_maintenance::E2

SVP, Maintenance & Protective Coatings Operations

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: E
Superfunction: manufacturing
Function: manufacturing_expansion
Family: maintenance
Universal level: 2 / 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) · E2review0.17

Lean Manufacturing · E2review0.17

Machine Shop · E2review0.17

Manufacturing Engineering · E2review0.17

Pilot Plant Operations · E2review0.17

Production Test · E2review0.17

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)