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Key statistics

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

4 of 8

Track

Executive

Family rungs priced

E1 · E2 · E3 · E4 · E5

—

industrial_energy_operations

Coordinates

2 / 4 spaces

pay@2 · 2026-07

What this role is

The most senior executive accountable for all land, property, and rights-of-way strategy across the organization's energy or mining assets. At the Senior Vice President (E4) level, the role owns multiple divisions, enterprise strategy and external stakeholders, and drives cross-division / enterprise. Leads division leaders.

What this level does

Oversees the full land/property portfolio across multiple strategic areas with high autonomy and corporate impact, integrating land-rights strategy into enterprise capital and development planning
Participates in enterprise strategic development — positioning the land and real-property estate as a strategic asset in decisions on generation mix, transmission expansion and renewable siting
Engages regularly with the board, CEO and industry leaders on land-acquisition risk, condemnation exposure and the property foundations of the enterprise's growth agenda
Directs cross-business land-rights, siting and regulatory strategy with broad organizational reach, aligning the property function to corporate objectives
Holds ultimate accountability for the enterprise's aggregate land, easement and right-of-way risk and the compliance framework governing it

Knowledge applied: Participates in enterprise strategic development, positioning the land and property estate as a strategic asset across multiple strategic areas.
Complexity & problem solving: Operates with high autonomy and corporate impact on cross-business land, siting and risk strategy.
Collaboration & interaction: Regular board, CEO and industry-leader engagement; broad organizational reach across business and functional lines.
Typical experience: 20+ years of extensive corporate strategy and executive leadership, including large land/property portfolios.

Skills at this level

Land-rights portfolio strategy: — Sets and governs acquisition and management strategy for right-of-way, easements and land rights across a project portfolio, broadening the function from acquiring individual rights to owning end-to-end project outcomes and land-use direction.
Property law and land-rights governance: — Directs the function's application of property law, land rights, permits, licenses, easements, legal contracts and real-estate/environmental regulations affecting building plans, setting standards that keep acquisitions defensible.
High-stakes acquisition negotiation: — Leads negotiation and persuasion with major property owners, coalitions and public bodies on high-value or contentious land acquisitions, reaching agreements that satisfy all parties while protecting cost and schedule.
Damage-settlement and dispute risk governance: — Sets authority thresholds and escalation frameworks for evaluating claims, negotiating damage settlements and resolving property-rights disputes, governing the function's aggregate settlement and litigation exposure.
Siting and site-suitability strategy: — Steers where the enterprise pursues solar, wind and infrastructure development by directing site-suitability analysis that weighs land use, climate conditions and grid connectivity against acquisition feasibility.
Title and property-records integrity oversight: — Establishes standards for title research and property ownership verification using online GIS, courthouse research and digital title tools so clean ownership is confirmed before construction commitments.
Regulatory compliance leadership: — Owns adherence to federal, state and local property, environmental and public-safety regulations across the land function, holding accountability for compliance gaps that stall or expose projects.
Cross-functional project-delivery coordination: — Integrates the land function with surveyors, engineers, appraisal, relocation and project-development teams to identify and secure the parcels required to deliver infrastructure programs.
Executive and board engagement: — Represents the land/property function to other executives, the board, CEO, regulators and industry leaders on land-risk, condemnation exposure and the property foundations of the enterprise growth agenda.
Land-asset value optimization: — Directs large-portfolio strategy that maximizes the value of company land and property assets while advising on land use and supporting infrastructure delivery that strengthens communities.

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

Land / Property — 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?

Employment growth 2014–2024, BLS OEWSobserved

+74.4%Managers, All Other · United States

361,900 → 630,980 jobs

BLS published no Managers, All Other employment before 2014 (this occupation code enters the OEWS series then), so the window shown is the widest one actually observed.

106,700 openings / year, split into:

replacement / exits 100,698

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: +4.5%
Growth share of hiring: 6%
Exit / retention pressure high: 94%
Openings / year: 106,700

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 it pays — by metro

OEWS metro median

San Jose-Sunnyvale-Santa Clara, CA$632k

San Francisco-Oakland-Fremont, CA$567k

Washington-Arlington-Alexandria, DC-VA-MD-WV$525k

Boulder, CO$518k

Seattle-Tacoma-Bellevue, WA$518k

Boston-Cambridge-Newton, MA-NH$496k

Lexington Park, MD$483k

Trenton-Princeton, NJ$480k

Pay only — metro-level demand isn't in public data (it needs job postings). National median $380k; 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 E4 (E4 — Senior Vice President) from the levels around it — this level only. Every word is real canon for this profile.

Scope: Multiple divisions
Autonomy: Owns cross-division strategy
Complexity: Enterprise strategy and external stakeholders
Impact: Cross-division / enterprise
Decision rights: Owns strategy and investment across divisions
Leadership: Leads division 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 E4 is E5.

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 Manager, Land & Property	jf_land_property::M4	$167,689†	confident0.06
Senior Land Agent	jf_land_property::P4	$109,466†	confident0.06
Advanced Land Technician	jf_land_property::S4	$56,408†	confident0.06
Chief Land Officer	jf_land_property::E3	$352,063†	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 11-9199

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

E4

jf_land_property::E4

Chief Land Officer

Land / Property

no content fingerprint

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: land_property
Universal level: 4 / 8

Content

content@2

What it's about— a fingerprint over the role's tasks & capabilities.

No content fingerprint for this profile.

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 · E4review0.17

Control Operations · E4review0.17

Emissions · E4review0.17

Energy Grid · E4review0.17

Energy Operations · E4review0.17

Mining Operations · E4review0.17

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 11-9199	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)