People Analytics Toolbox

Ask about this role

grounded in this role's JobFrame record + structure

Download this job's description (markdown) → derived live from this record.

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

17-0000

manufacturing

Coordinates

3 / 4 spaces

pay@2 · 2026-07

What this role is

Manages a team of manufacturing engineers responsible for developing and improving production processes, equipment, and supplier qualification for a product line or facility area. 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

Manages the manufacturing engineering department for a value stream or plant area, responsible for its operations and budget across diverse process and equipment issues
Evaluates production trends (yield, cycle time, variance data) to prioritize which processes to re-engineer and where to invest in new manufacturing methods
Leads cross-functional teams through NPIs, integrating design, quality, and operations to move new products into stable volume production
Sets standards for troubleshooting, tolerance changes, and lean strategy adoption, holding the team accountable for measurable efficiency and quality gains

Knowledge applied: Applies trend analysis and diverse process knowledge to run a department and prioritize re-engineering investments.
Complexity & problem solving: Addresses diverse issues by evaluating production trends and directing complex NPI and process programs.
Collaboration & interaction: Leads functional and cross-functional NPI teams and engages internal customers.
Typical experience: 5–7+ years managing manufacturing professionals and budgets.

Skills at this level

Lean Manufacturing: — Reduces waste and increases production efficiency across manufacturing cells; forms the foundational discipline for planning and standardizing how a manufacturing engineering team runs process improvements.
Manufacturing Process Development: — Develops new manufacturing methods, selects and maintains production equipment, and standardizes processes to improve existing operations and support production ramps.
Root Cause Analysis and Troubleshooting: — Determines root causes of product or process failures and recommends changes in designs, tolerances, or processing; troubleshoots new or existing product problems involving designs, materials, or processes.
Operational Problem Resolution: — Investigates and resolves shop-floor operational problems such as material-use variances and line bottlenecks to protect throughput and yield.
New Product Introduction (NPI): — Supports and coordinates the transfer of new products into production, aligning manufacturing methods, equipment, and documentation with design and ramp timelines.
Analysis and Problem-Solving: — Analyzes manufacturing problems from multiple perspectives and explores creative solutions, with troubleshooting of processes and machinery central to the work.
CAM Software: — Uses computer-aided manufacturing software to translate designs into machine tool paths and production programs for the factory floor.
PLM Software: — Uses product lifecycle management software to control manufacturing process documentation, engineering changes, and configuration across a product line.
CAD (AutoCAD / CATIA / SolidWorks / Creo): — Uses AutoCAD, CATIA, SolidWorks, or Creo Parametric to design fixtures, tooling, and process layouts and to review product geometry for manufacturability.
Capital Equipment and Budget Management: — Plans and manages manufacturing engineering budgets and capital equipment investments, prioritizing spend against efficiency, capacity, and quality gains.

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

Manufacturing Engineering — 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 17-0000 · national

Employment growth 2019–2024, BLS OEWSobserved

+20.1%Industrial Engineers · United States

291,710 → 350,230 jobs

25,200 openings / year, split into:

growth 3,862

replacement / exits 21,338

Growth — new jobs (15%)Exits — backfill (85%)

15% of hiring here is genuine expansion; the rest backfills people who move on.

Projected growth 2024–34 expanding: +11.0%
Growth share of hiring: 15%
Exit / retention pressure moderate: 85%
Openings / year: 25,200

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 Manufacturing Officer	jf_manufacturing_engineering::E3	$363,257	confident0.06
Manufacturing Engineer	jf_manufacturing_engineering::P3	$85,090	confident0.06
Senior Manufacturing Technician	jf_manufacturing_engineering::S3	$51,142	confident0.06
Senior Supervisor, Manufacturing Engineering	jf_manufacturing_engineering::M2	$113,967	confident0.06

Capability cluster

O*NET 17-2112

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_manufacturing_engineering::M3

Manufacturing Engineering Manager

Manufacturing Engineering

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: manufacturing
Function: manufacturing_expansion
Family: manufacturing_engineering
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) · M3review0.17

Lean Manufacturing · M3review0.17

Machine Shop · M3review0.17

Maintenance · M3review0.17

Pilot Plant Operations · M3review0.17

Production Test · 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 17-2112	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)