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.

5 of 8

Track

Support

Family rungs priced

S1 · S2 · S3 · S4 · S5

—

industrial_energy_operations

Coordinates

2 / 4 spaces

pay@2 · 2026-07

What this role is

Senior individual-contributor land professional who leads complex land acquisition, leasing, and title matters for energy or mining projects. At the Principal Support Specialist (S5) level, the role owns function-wide support practice, program-level and systemic support problems, and drives support strategy across the function. Subject-matter authority; shapes the practice.

What this level does

Create and document standardized land-records and title-research procedures — run-sheet formats, curative checklists, document-package standards — for adoption across the land-support group
Handle the most complex title and records situations, developing the research approach for tangled heirship, competing claims, and multi-jurisdiction rights-of-way that others cannot resolve
Define how GIS parcel layers, land records, and acquisition-document systems reconcile, and set the data conventions the support team follows
Act as working lead and go-to authority for land-support staff across projects, facilitating execution, resolving escalated records questions, and training on new procedures
Advise agents and cross-functional teams (Regulatory, Lease Records, Accounting) on records feasibility and title-support methods when scoping novel acquisitions

Knowledge applied: Highly skilled in land-records and title-support methods; contributes to creating the procedures, data conventions, and checklists the group uses.
Complexity & problem solving: Develops research approaches for the most complex title and records situations; resolves escalated issues others cannot.
Collaboration & interaction: Acts as working lead and facilitator across projects; provides peer guidance, trains staff, and advises agents and cross-functional teams.
Typical experience: 6+ years; expert in land-records support and title research.

Skills at this level

Title Research & Chain of Title: — Traces ownership through recorded deeds and courthouse indexes, building run sheets that document chain of title with instrument numbers and recording dates to confirm who holds the parcel.
Run Sheet & Ownership Report Preparation: — Compiles run sheets, property reports, and mineral-ownership and lien listings for a project tract, presenting research findings in the format acquisition agents rely on.
Liens, Minerals & Easement Identification: — Reads legal descriptions to identify existing liens, mineral interests, and prior easements affecting a parcel, and flags encumbrances that could impede acquisition.
Easement & Access Agreement Documentation: — Assembles and drafts easement, temporary-workspace, and access-agreement documents from standard forms, populating legal descriptions, parties, and compensation figures for agent review.
Digital Title Verification: — Uses digital title-verification systems to check property ownership records and reconciles discrepancies against source deeds so access rights for infrastructure projects are accurate and timely.
GIS Parcel Records: — Enters and maintains parcel data, ownership, and easement layers in GIS so land records stay reconciled with acquisition documents through recording.
Right-of-Way Regulatory Literacy: — Applies federal, state, and local recording and right-of-way requirements to document packages and filing steps, adjusting for the rules of a given jurisdiction or agency.
Land Records Reconciliation: — Cross-checks ownership, acreage, appraisal figures, and legal descriptions across Lease Records, Division Order, and Regulatory files to catch and resolve inconsistencies before transactions proceed.
Landowner Correspondence Handling: — Logs and tracks landowner outreach — survey-permission requests, mailings, and signature returns — routing inquiries and maintaining accurate contact and status records per parcel.
Land-Support Procedure Development: — Creates and documents standardized run-sheet formats, curative checklists, and document-package standards for adoption across the land-support group.

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

+20.7%Business Operations Specialists, All Other · United States

934,370 → 1,128,200 jobs

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

108,200 openings / year, split into:

replacement / exits 104,583

Growth — new jobs (3%)Exits — backfill (97%)

3% of hiring here is genuine expansion; the rest backfills people who move on.

Projected growth 2024–34 expanding: +3.0%
Growth share of hiring: 3%
Exit / retention pressure high: 97%
Openings / year: 108,200

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 it pays — by metro

OEWS metro median

San Jose-Sunnyvale-Santa Clara, CA$99k

San Francisco-Oakland-Fremont, CA$88k

Washington-Arlington-Alexandria, DC-VA-MD-WV$82k

Boulder, CO$81k

Seattle-Tacoma-Bellevue, WA$81k

Boston-Cambridge-Newton, MA-NH$77k

Lexington Park, MD$75k

Trenton-Princeton, NJ$75k

Pay only — metro-level demand isn't in public data (it needs job postings). National median $59k; 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 S5 (S5 — Principal Support Specialist) from the levels around it — this level only. Every word is real canon for this profile.

Scope: Function-wide support practice
Autonomy: Sets direction for the support discipline
Complexity: Program-level and systemic support problems
Impact: Support strategy across the function
Decision rights: Authority over support practice and standards
Leadership: Subject-matter authority; shapes the practice

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

Promotion

S5is the top of this family's ladder — progression from here is a lattice move (see adjacent roles below), not a rung.

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 Land Officer	jf_land_property::E5	$340,737†	confident0.06
Director of Land and Property	jf_land_property::M5	$188,371†	confident0.06
Expert Land Agent	jf_land_property::P5	$138,423†	confident0.06
Advanced Land Technician	jf_land_property::S4	$56,408†	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 13-1199

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

S5

jf_land_property::S5

Lead Land Agent

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: S
Superfunction: industrial_energy_operations
Function: energy_utilities_business_operations
Family: land_property
Universal level: 5 / 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 · S5review0.17

Control Operations · S5review0.17

Emissions · S5review0.17

Energy Grid · S5review0.17

Energy Operations · S5review0.17

Mining Operations · S5review0.17

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 13-1199	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)