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Key statistics

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

2 of 8

Track

Executive

Family rungs priced

E1 · E2 · E3 · E4

17-0000

industrial_energy_operations

Coordinates

3 / 4 spaces

pay@2 · 2026-07

What this role is

Executive leader responsible for the enterprise-wide surveying, mapping, and spatial-data strategy supporting oil and gas project planning and land management. At the Senior Director (Executive) (E2) level, the role owns multiple functions or a major area, multi-function strategy and risk, and drives major-area outcomes. Leads function leaders.

What this level does

Leads multiple functions or divisions through VPs — for example combining geomatics with adjacent geoscience, engineering-services, or data-platform units — resolving cross-functional, high-consequence trade-offs between field operations, data processing, and analytical delivery
Directs the enterprise geospatial data strategy so that databases across office, cloud, and archive reflect real-time project status and support multiple business lines simultaneously
Makes resourcing and technology-investment decisions (survey fleets, drone/LiDAR programs, GIS platform standardization) whose scale and cost can materially affect divisional viability
Negotiates critical commercial and delivery matters with top leaders and major customers, positioning geospatial capability as a differentiator across the served markets
Shapes how buffer-overlay and pattern analysis feed decision-making for urban planning, environmental impact assessment, and transportation optimization across the divisions under remit

Knowledge applied: Applies cross-functional judgment across geomatics and adjacent divisions, using abstract, high-consequence reasoning about how spatial-data capability serves multiple business lines.
Complexity & problem solving: Resolves cross-functional issues where trade-offs between field operations, data processing, platform investment, and delivery can impact company viability.
Collaboration & interaction: Negotiates critical commercial and delivery matters with top leaders and major customers; leads VPs across functions or a significant business unit.
Typical experience: 15+ years including strategic leadership of geospatial functions or units, with proven cross-divisional accountability.

Skills at this level

Geospatial Function Strategy: — Sets and governs the organization's strategy for GIS platforms, spatial-data acquisition, and survey delivery, deciding how geospatial capability is standardized and scaled across projects and business lines.
Spatial Data Integrity Governance: — Establishes and holds accountability for QA/QC standards that keep geospatial databases across office, cloud, and archive systems accurate and reflective of real-time project status, treating data-integrity failure as an enterprise risk.
Reality Capture & Digital Twin Leadership: — Directs high-precision survey and reality-capture programs — terrestrial and SLAM-based mobile scanning, LiDAR, and dimensional control — that feed engineering design, construction verification, as-built documentation, and digital-twin workflows.
Customer Requirement Translation: — Evaluates and translates customer requirements, business goals, and strategies into geospatial business solutions, acting as the senior trusted adviser between clients and the geomatics function.
Geospatial Platform Evolution: — Broadens the reach of GIS technology across the organization and shapes the evolution of the geospatial platform so it serves expanding business needs.
Survey Field Operations Oversight: — Governs conventional and advanced field operations — GNSS, bathymetry, multibeam/side-scan sonar, sub-bottom profiler, and control-network capture — on moderate-to-large complex infrastructure and industrial projects.
Geospatial Analytics for Decision-Making: — Directs the use of buffer-overlay and pattern analysis on spatial datasets to inform urban planning, environmental impact assessment, and transportation optimization outcomes.
Executive Stakeholder & Board Engagement: — Engages boards, CEOs, and industry leaders to position geospatial and reality-capture capability as corporate advantage, and represents the organization externally on geospatial strategy.

Model-authored from 18 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

Geomatics — 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 17-0000 · national

Employment growth 2019–2024, BLS OEWSobserved

+13.2%Cartographers and Photogrammetrists · United States

11,300 → 12,790 jobs

1,000 openings / year, split into:

replacement / exits 914

Growth — new jobs (9%)Exits — backfill (91%)

9% of hiring here is genuine expansion; the rest backfills people who move on.

Projected growth 2024–34 expanding: +6.4%
Growth share of hiring: 9%
Exit / retention pressure high: 91%
Openings / year: 1,000

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 E2 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$524k

San Francisco-Oakland-Fremont, CA$470k

Washington-Arlington-Alexandria, DC-VA-MD-WV$435k

Boulder, CO$429k

Seattle-Tacoma-Bellevue, WA$429k

Boston-Cambridge-Newton, MA-NH$411k

Lexington Park, MD$400k

Trenton-Princeton, NJ$398k

Pay only — metro-level demand isn't in public data (it needs job postings). National median $315k; 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 E2 (E2 — Senior Director (Executive)) from the levels around it — this level only. Every word is real canon for this profile.

Scope: Multiple functions or a major area
Autonomy: Owns area-level strategy
Complexity: Multi-function strategy and risk
Impact: Major-area outcomes
Decision rights: Owns strategy and resourcing across functions
Leadership: Leads function 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 E2 is E3.

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 Geomatics Supervisor	jf_geomatics::M2	$110,455†	confident0.06
Geomatics Analyst	jf_geomatics::P2	$72,357†	confident0.06
Geomatics Technician	jf_geomatics::S2	$42,923†	confident0.06
VP, Geomatics	jf_geomatics::E1	$169,459†	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 17-1021

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

E2

jf_geomatics::E2

SVP of Geomatics

Geomatics

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: geoscience
Family: geomatics
Universal level: 2 / 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").

Geology · E2review0.17

Geophysics · E2review0.17

Geothermal · E2review0.17

Petrophysics · E2review0.17

Technologist · E2review0.17

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 17-1021	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)