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Key statistics

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

3 of 8

Track

Individual contributor

Family rungs priced

P1 · P2 · P3 · P4 · P5 · P6 · P7

19-0000

industrial_energy_operations

Coordinates

3 / 4 spaces

pay@2 · 2026-07

What this role is

Career-level individual contributor who performs surveying, mapping, and spatial-data analysis to support oil and gas project planning and land management. At the Mid-Level Professional (P3) level, the role owns features or a sub-system end-to-end, adapts existing approaches, and drives project / team outcomes. Mentors juniors informally.

What this level does

Take independent responsibility for parts of a project — planning field investigations, interpreting data, and being accountable for defined deliverables under milestone review
Develop and manage large spatial and attribute data sets (e.g., digital imagery, LiDAR, InSAR), including their structure, standards, and integrity
Prepare client-ready reports, manage portions of a project budget, and coordinate with regulators or contractors
Ensure data collection and analysis comply with industry standards and regulations, resolving routine compliance issues independently
Train junior technicians and coordinate day-to-day project activities across field and office environments

Knowledge applied: Applies specialized geospatial data-management and analysis knowledge (large LiDAR/InSAR/imagery datasets) independently across diverse project work.
Complexity & problem solving: Evaluates identifiable factors to interpret data and plan investigations; accountable for defined project components.
Collaboration & interaction: Networks with senior professionals, regulators, and contractors; coordinates project activities and trains juniors.
Typical experience: 5+ years (BA), 3 years (MA); or provincial geomatics certification where regulated.

Skills at this level

Geographic Information Systems (GIS): — Manages, maps, and analyzes spatially referenced data using GIS platforms such as ArcGIS and QGIS to produce and interpret geospatial deliverables.
Computer-Aided Design (CAD) Survey Drafting: — Produces legal and engineering survey products — plans, drawings, and mapping outputs — to specification using CAD techniques.
Field Survey Instrumentation: — Operates survey instruments in the field and processes the resulting survey data to produce plans that meet required tolerances and specification.
LiDAR, InSAR and Digital Imagery Processing: — Develops and manages large spatial and attribute datasets from LiDAR, InSAR, and digital imagery sources, ensuring their structure, standards, and integrity.
Spatial Data QA/QC: — Performs quality assurance and quality control of spatial data against industry standards and documented procedures to ensure accuracy and compliance.
Geospatial Project Management: — Manages geomatics projects across procurement, acquisition, production, and QA/QC, coordinating field and office work and portions of a budget.
Geospatial Data Standards & Regulatory Compliance: — Ensures data collection and analysis comply with industry standards and regulations, and defines data management standards for datasets and products.
Applied Spatial Analysis & Modelling: — Applies analytical and modelling methods to interpret geospatial data, reconcile multi-sensor datasets, and advise on data application and interpretation.
Technical Reporting & Stakeholder Consultation: — Prepares client-ready reports and presentations of spatial analyses and consults interdisciplinary stakeholders and clients to gather feedback and resolve issues.
GIS User Support & Training: — Provides technical support and training to technical and non-technical users on the operation and application of geographic information systems.

Model-authored from 21 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 19-0000 · national

Employment growth 2019–2024, BLS OEWSobserved

-22.9%Geoscientists, Except Hydrologists and Geographers · United States

29,200 → 22,510 jobs

2,000 openings / year, split into:

replacement / exits 1,919

Growth — new jobs (4%)Exits — backfill (96%)

4% of hiring here is genuine expansion; the rest backfills people who move on.

Projected growth 2024–34 expanding: +3.2%
Growth share of hiring: 4%
Exit / retention pressure high: 96%
Openings / year: 2,000

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 P3 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$134k

San Francisco-Oakland-Fremont, CA$120k

Washington-Arlington-Alexandria, DC-VA-MD-WV$111k

Boulder, CO$110k

Seattle-Tacoma-Bellevue, WA$110k

Boston-Cambridge-Newton, MA-NH$105k

Lexington Park, MD$102k

Trenton-Princeton, NJ$102k

Pay only — metro-level demand isn't in public data (it needs job postings). National median $80k; 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 P3 (P3 — Mid-Level Professional) from the levels around it — this level only. Every word is real canon for this profile.

Scope: Features or a sub-system end-to-end
Autonomy: Works independently on standard work; reviewed on the non-standard
Complexity: Diverse problems; adapts existing approaches
Impact: Project / team outcomes
Decision rights: Owns implementation decisions for own scope
Leadership: Mentors juniors informally

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

Promotion

The next rung from P3 is P4.

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 Geomatics Officer	jf_geomatics::E3	$352,063†	confident0.06
Geomatics Manager	jf_geomatics::M3	$120,351†	confident0.06
Senior Survey Technician	jf_geomatics::S3	$49,566†	confident0.06
Geomatics Analyst	jf_geomatics::P2	$72,357†	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 19-2042

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

P3

jf_geomatics::P3

Geomatics Analyst

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: P
Superfunction: industrial_energy_operations
Function: geoscience
Family: geomatics
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").

Geology · P3review0.17

Geophysics · P3review0.17

Geothermal · P3review0.17

Petrophysics · P3review0.17

Technologist · P3review0.17

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 19-2042	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)