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Key statistics

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

1 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

Entry-level individual contributor who assists with surveying, mapping, and spatial-data collection for oil and gas projects. At the Support Associate (S1) level, the role owns a single task type or queue, routine, well-defined requests, and drives individual transactions. None.

What this level does

Gather and verify spatial data from prescribed sources such as satellite imagery, GNSS logs and geological surveys, following specific instructions for each dataset
Clean and enter incoming spatial records into existing geospatial databases, checking field values against a checklist to ensure integrity and accuracy
Generate standard maps and basic layouts in ArcGIS or QGIS from templates provided by a lead
Compile routine reports and dashboard outputs using established procedures, flagging anything unusual to a senior for review

Knowledge applied: General knowledge of geospatial data-entry and mapping routines; applies prescribed steps in ArcGIS/QGIS and database checklists.
Complexity & problem solving: Routine tasks with readily available answers; escalates anything unusual in the data.
Collaboration & interaction: Standard interactions with a lead who assigns work; completes own tasks.
Typical experience: 0–1 years; minimal experience.

Skills at this level

Spatial data collection and verification: — Gathers and verifies spatial data from sources such as GNSS, satellite imagery and geological surveys, checking field values to ensure database integrity and accuracy.
Geospatial database management: — Builds and maintains geodatabases with multiple inputs, reconciling GPS and remote-sensing sources and resolving attribute, projection and topology conflicts.
Geoprocessing and spatial analysis: — Runs analytical techniques such as buffer-overlay analysis in ArcGIS or QGIS to identify patterns for urban planning, environmental impact and transportation datasets.
Cartographic production and QA: — Produces maps, dashboards and report deliverables to style standards, and performs quality assurance by comparing outputs against source data to catch accuracy and metadata errors.
Geospatial scripting and automation: — Writes Python or FME scripts to automate repetitive geoprocessing and data-cleaning steps within the team's mapping pipelines.
Remote-sensing data handling: — Processes satellite imagery and aerial photography (e.g. in ERDAS Imagine) as supplementary sources for mapping and analysis tasks.
Project coordination and tracking: — Coordinates the sequencing and delivery of mapping tasks and QA across a project, tracking progress against deadlines and priorities.
Technical communication: — Explains data assessments, analytical results and recommendations in written reports and presentations to engineers, project managers and other GIS staff.
Procedure development and training: — Establishes new data-handling and geoprocessing standards for the group and trains less experienced technicians in their application.

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

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?

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 S1 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$61k

San Francisco-Oakland-Fremont, CA$54k

Washington-Arlington-Alexandria, DC-VA-MD-WV$50k

Boulder, CO$50k

Seattle-Tacoma-Bellevue, WA$50k

Boston-Cambridge-Newton, MA-NH$48k

Lexington Park, MD$46k

Trenton-Princeton, NJ$46k

Pay only — metro-level demand isn't in public data (it needs job postings). National median $36k; 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 S1 (S1 — Support Associate) from the levels around it — this level only. Every word is real canon for this profile.

Scope: A single task type or queue
Autonomy: Close supervision; follows defined procedures
Complexity: Routine, well-defined requests
Impact: Individual transactions
Decision rights: Acts within scripts; escalates exceptions
Leadership: None

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

Promotion

The next rung from S1 is S2.

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
VP, Geomatics	jf_geomatics::E1	$169,459†	confident0.06
Geomatics Supervisor	jf_geomatics::M1	$85,619†	confident0.06
Geomatics Associate	jf_geomatics::P1	$61,862†	confident0.06
Geomatics Technician	jf_geomatics::S2	$42,923†	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

S1

jf_geomatics::S1

Geomatics Technician

Geomatics

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: geoscience
Family: geomatics
Universal level: 1 / 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").

Geology · S1review0.17

Geophysics · S1review0.17

Geothermal · S1review0.17

Petrophysics · S1review0.17

Technologist · S1review0.17

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)