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Key statistics

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

1 of 8

Track

Executive

Family rungs priced

E1 · E2 · E3 · E4 · E5

11-0000

industrial_energy_operations

Coordinates

3 / 4 spaces

pay@2 · 2026-07

What this role is

Executive leader who owns market development and customer origination strategy for the company's energy or mining output across a defined region. At the Director (Executive) (E1) level, the role owns a significant function with strategic authority, strategic and cross-functional, and drives function-wide enterprise impact. Executive leadership of a function.

What this level does

Lead the origination sub-function through Director/M5-level originator managers, owning the commercial lifecycle of a clean-energy portfolio (renewable power, storage, environmental products) across upstream and downstream activities
Set the origination strategy for the sub-function's counterparty segment (utilities, munis, co-ops, generators), establishing the deal-quality bar and execution standards individual originators and structurers work to
Serve as the senior commercial escalation point for high-value PPA, tolling and offtake negotiations, personally shepherding the most complex transactions to closing where functional consequences are serious
Direct the working partnership with Engineering, Finance, Legal and Development to design competitive offerings and ensure optimal risk allocation across the deal pipeline
Govern the energy-data and reporting discipline underpinning deals — ensuring consumption/cost data, market analysis and management reporting are robust enough to support commercial recommendations

Knowledge applied: Applies deep origination and energy/utility industry knowledge to set functional commercial strategy; requires detailed knowledge of the company's counterparty base (utilities, munis, co-ops, generators) and its deal portfolio, including the energy-data and market-analysis foundation behind deals.
Complexity & problem solving: Resolves complex individual and portfolio-level deal problems — escalated PPA/tolling/offtake negotiations, risk allocation across Engineering/Finance/Legal — with serious functional and business consequences.
Collaboration & interaction: Interfaces with other executives and major counterparties; leads cross-functional deal teams and represents origination in enterprise commercial reviews.
Typical experience: 12–15+ years of origination/commercial and management experience in energy, including leadership of originators.

Skills at this level

Energy market analysis and forecasting: — Reads energy market dynamics by pulling data from multiple sources and analyzing energy consumption and cost trends and anomalies, converting findings into market insights and commercial recommendations for deal teams and counterparties.
Deal structuring and commercial negotiation: — Leads origination, structuring and execution of PPAs, tolling and offtake agreements — negotiating supply and ownership terms from initiation to executed contract and shepherding transactions to closing with optimal risk allocation.
Credit and risk evaluation: — Evaluates transaction risk and credit exposure by reading indentures and credit agreements, conducting due diligence, and developing recommendations that keep counterparty concentration and structure within the firm's risk appetite.
Counterparty relationship management: — Owns the primary commercial relationship with utilities, munis, co-ops, generators, corporates and hyperscalers, structuring deals around their needs and serving as the accountable point of contact across the transaction lifecycle.
First-of-kind commercial architecture: — Architects novel commercial structures for emerging counterparty types (e.g., large loads, hyperscalers) and leads complex utility tariff negotiations, setting and holding a consistently high deal-execution standard across the team.
Regulatory and industry research: — Tracks energy trends, technologies and regulatory/tariff developments, researching public information to inform commercial decisions and long-tenor commitment strategy.
Energy procurement and supply-chain structuring: — Structures upstream and downstream procurement across power, storage and environmental products so that supply commitments are optimally allocated across the clean-energy portfolio.

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

Origination — 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

+49.3%General and Operations Managers · United States

2,400,280 → 3,584,420 jobs

308,700 openings / year, split into:

replacement / exits 292,364

Growth — new jobs (5%)Exits — backfill (95%)

5% of hiring here is genuine expansion; the rest backfills people who move on.

Projected growth 2024–34 expanding: +4.4%
Growth share of hiring: 5%
Exit / retention pressure high: 95%
Openings / year: 308,700

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 E1 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$275k

San Francisco-Oakland-Fremont, CA$247k

Washington-Arlington-Alexandria, DC-VA-MD-WV$228k

Boulder, CO$225k

Seattle-Tacoma-Bellevue, WA$225k

Boston-Cambridge-Newton, MA-NH$216k

Lexington Park, MD$210k

Trenton-Princeton, NJ$209k

Pay only — metro-level demand isn't in public data (it needs job postings). National median $165k; 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 E1 (E1 — Director (Executive)) from the levels around it — this level only. Every word is real canon for this profile.

Scope: A significant function with strategic authority
Autonomy: Sets functional strategy
Complexity: Strategic and cross-functional
Impact: Function-wide enterprise impact
Decision rights: Owns strategy and investment for the function
Leadership: Executive leadership of a function

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

Promotion

The next rung from E1 is E2.

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
Origination Supervisor	jf_origination::M1	$85,619†	confident0.06
Origination Associate	jf_origination::P1	$61,862†	confident0.06
Origination Support Coordinator	jf_origination::S1	$37,323†	confident0.06
SVP, Origination	jf_origination::E2	$322,728†	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 11-1021

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

E1

jf_origination::E1

VP, Origination

Origination

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: industrial_energy_operations
Function: energy_utilities_business_operations
Family: origination
Universal level: 1 / 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").

Assets · E1review0.17

Control Operations · E1review0.17

Emissions · E1review0.17

Energy Grid · E1review0.17

Energy Operations · E1review0.17

Land / Property · E1review0.17

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 11-1021	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)