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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

11-0000

industrial_energy_operations

Coordinates

3 / 4 spaces

pay@2 · 2026-07

What this role is

Leads a team of chemical engineers responsible for designing and improving processes used to manufacture chemicals, fuels, and related products. 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

Leads a chemical engineering department or functional team, responsible for its operations and budget across a portfolio of process-facility and optimization projects.
Evaluates diverse process issues and trends across multiple production lines, guiding engineers on sizing, specifying, and procuring equipment.
May lead other managers or cross-functional professionals coordinating engineering design, construction support, and process startups with vendors and clients.
Owns capital project management for the department — scoping, scheduling, and resourcing process-facility projects to meet regulatory and safety requirements.
Establishes and enforces technical standards, safety procedures, and FDA-compliant manufacturing practices for the department's processes.

Knowledge applied: Applies broad process-engineering and capital-project knowledge to run a department; may lead managers or cross-functional professionals.
Complexity & problem solving: Addresses diverse process issues across lines, evaluating trends to guide equipment and design decisions.
Collaboration & interaction: Leads functional engineering or client-facing teams; coordinates with vendors and clients on design and startups.
Typical experience: 5–7+ years managing professionals and budgets.

Skills at this level

Process Troubleshooting and Root-Cause Analysis: — Determines the causes of operational problems or failures in chemical and biological processes, diagnosing equipment and system issues and directing corrective action to restore safe, compliant operation.
Equipment Sizing, Specification and Procurement: — Evaluates the characteristics of process equipment and systems, then sizes, specifies, and procures equipment for process-facility projects to meet performance and safety requirements.
Process Optimization: — Improves chemical manufacturing processes by evaluating process and data characteristics, refining procedures, and advancing techniques to increase yield, quality, and cost efficiency.
Capital Project Management: — Manages process-facility capital projects from engineering design and equipment procurement through construction support and process startup, coordinating vendors and clients.
Regulatory Compliance and Risk Assessment: — Performs regulatory compliance reviews and risk assessments to ensure processes and manufacturing operations meet FDA and applicable safety requirements.
Safety Standards and Procedure Development: — Develops and enforces safety standards, policies, and procedures and creates technical methods and processes governing safe operation of chemical processes.
Process Simulation and Modeling: — Applies process simulation tools such as Aspen HYSYS, CHEMCAD, and COMSOL Multiphysics to model chemical processes, evaluate designs, and predict process behavior before implementation.
Engineering Team Leadership and Mentoring: — Supervises, mentors, and develops engineering team members, building process-engineering capability and coordinating engineers across projects.
Analytical and Problem-Solving Skills: — Evaluates designs and processes and proposes improvements where necessary, using logic and reasoning to weigh alternative solutions and approaches.
Technical Vision and Innovation Strategy: — Defines technical vision, innovation strategy, and high-level engineering standards, evaluating new developments in the field to guide direction across multiple teams or the engineering organization.
Creativity / Innovation: — Explores new ways of applying chemical engineering to invent materials and advance manufacturing techniques, applying creative problem-solving when designs do not work the first time.

Model-authored from 20 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

Chemical — 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 11-0000 · national

Employment growth 2019–2024, BLS OEWSobserved

+8.3%Architectural and Engineering Managers · United States

194,250 → 210,340 jobs

14,500 openings / year, split into:

replacement / exits 13,693

Growth — new jobs (6%)Exits — backfill (94%)

6% of hiring here is genuine expansion; the rest backfills people who move on.

Projected growth 2024–34 expanding: +3.8%
Growth share of hiring: 6%
Exit / retention pressure high: 94%
Openings / year: 14,500

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$201k

San Francisco-Oakland-Fremont, CA$180k

Washington-Arlington-Alexandria, DC-VA-MD-WV$166k

Boulder, CO$164k

Seattle-Tacoma-Bellevue, WA$164k

Boston-Cambridge-Newton, MA-NH$157k

Lexington Park, MD$153k

Trenton-Princeton, NJ$152k

Pay only — metro-level demand isn't in public data (it needs job postings). National median $120k; 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 Chemical Officer	jf_chemical::E3	$352,063†	confident0.06
Chemical Engineer	jf_chemical::P3	$82,468†	confident0.06
Senior Chemical Process Technician	jf_chemical::S3	$49,566†	confident0.06
Senior Supervisor, Chemical Process Engineering	jf_chemical::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 11-9041

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_chemical::M3

Chemical Engineering Manager

Chemical

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: engineering_expansion
Family: chemical
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").

Aeronautical · M3review0.17

Agricultural · M3review0.17

Agronomist · M3review0.17

Application Services · M3review0.17

Communication · M3review0.17

Electrical Engineering · 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 11-9041	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)