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Key statistics

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

3 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

Experienced technical specialist who performs advanced hands-on operational tasks supporting energy production, gas, power, or offshore facilities. At the Senior Support Specialist (S3) level, the role owns escalated / complex cases, complex or non-standard cases, and drives resolution quality on the team's hardest cases. Guides junior support informally.

What this level does

Analyze properties within the portfolio for trends and anomalies in energy consumption, using judgment to determine which variances warrant investigation versus which are seasonal
Support Energy Imbalance Market operations by analyzing operational information independently and responding to routine operational needs without step-by-step instruction
Coordinate daily utility operations for senior Utility Managers, sequencing maintenance scheduling and compliance tracking across multiple properties
Manage customer data flow through credit approval, risk/product review, and settlements steps, resolving non-routine data exceptions using detailed knowledge of the procedures
Interview client contacts to gather and document straightforward business requirements and perform basic process mapping for recurring energy operations tasks

Knowledge applied: Detailed knowledge of consumption analysis and customer data-flow procedures sufficient to perform non-routine tasks like anomaly investigation and settlement exception handling.
Complexity & problem solving: Makes judgments on moderately difficult tasks — deciding which consumption variances warrant investigation and resolving data exceptions.
Collaboration & interaction: Substantial procedural understanding; coordinates daily utility operations tasks with little instruction on the routine work.
Typical experience: 2–4 years; skilled in energy operations support.

Skills at this level

Energy Consumption Data Management: — Collects utility bills and meter readings and maintains the accuracy of consumption records including square footage, equipment inventories, and weather-normalization fields across a property portfolio.
Consumption Trend and Anomaly Analysis: — Reviews energy usage across portfolio properties to detect trends and anomalies, distinguishing seasonal or weather-driven variance from genuine irregularities that need investigation.
Utility Budget Preparation Support: — Compiles historical consumption to assist in generating utility budgets and calculates projected energy savings using established workbooks and templates.
Customer Data-Flow Processing: — Manages customer data across energy operations — initial account set-up, credit approval, risk/product review, pricing, and contract records — moving data cleanly through CIS/Billing and EDI systems.
Settlements and Billing Reconciliation: — Reconciles utility bills against meter readings and works through settlement exceptions, correcting discrepancies that span billing and market-operations records.
CIS/Billing and EDI Systems Knowledge: — Applies working familiarity with CIS/Billing, EDI, and Customer Care systems to enter, retrieve, and correct C&I and Mass Market product data in energy operations.
Energy Imbalance Market Operations Support: — Analyzes Energy Imbalance Market operational information and responds to day-to-day operational needs, feeding accurate data into the operations cycle.
Compliance Documentation Administration: — Organizes, tracks, and follows up on utility compliance documentation and maintenance schedules so records are complete and retrievable for scheduled reviews.
Business Requirements Gathering: — Interviews client contacts to document business requirements for energy operations tasks and performs basic process mapping of recurring workflows.
Procedure Development and Documentation: — Creates and documents new energy operations procedures, templates, and data-validation checks, standardizing how the support team handles complex or newly-regulated cases.
Stakeholder Communication: — Coordinates with clients, utility representatives, and contractors on data corrections and incentive-program requirements, and produces clear operational reports from consumption and billing figures.
Working-Lead Coordination: — Sequences and reviews the support team's data, budgeting, and reconciliation tasks, coaching less experienced analysts on energy operations procedures without holding formal management authority.

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

Energy Operations — 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

+23.2%Plant and System Operators, All Other · United States

12,950 → 15,950 jobs

1,600 openings / year, split into:

replacement / exits 1,574

Growth — new jobs (2%)Exits — backfill (98%)

2% of hiring here is genuine expansion; the rest backfills people who move on.

Projected growth 2024–34 expanding: +1.6%
Growth share of hiring: 2%
Exit / retention pressure high: 98%
Openings / year: 1,600

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$81k

San Francisco-Oakland-Fremont, CA$72k

Washington-Arlington-Alexandria, DC-VA-MD-WV$67k

Boulder, CO$66k

Seattle-Tacoma-Bellevue, WA$66k

Boston-Cambridge-Newton, MA-NH$63k

Lexington Park, MD$61k

Trenton-Princeton, NJ$61k

Pay only — metro-level demand isn't in public data (it needs job postings). National median $48k; 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 S3 (S3 — Senior Support Specialist) from the levels around it — this level only. Every word is real canon for this profile.

Scope: Escalated / complex cases
Autonomy: Limited supervision
Complexity: Complex or non-standard cases
Impact: Resolution quality on the team's hardest cases
Decision rights: Owns escalation resolution within policy
Leadership: Guides junior support 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 S3 is S4.

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 Operating Officer, Energy Operations	jf_energy_operations::E3	$352,063†	confident0.06
Energy Operations Manager	jf_energy_operations::M3	$120,351†	confident0.06
Energy Operations Analyst	jf_energy_operations::P3	$82,468†	confident0.06
Energy Operations Analyst	jf_energy_operations::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 51-8099

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

S3

jf_energy_operations::S3

Senior Energy Operations Technician

Energy Operations

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: energy_operations
Universal level: 3 / 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 · S3review0.17

Control Operations · S3review0.17

Emissions · S3review0.17

Energy Grid · S3review0.17

Land / Property · S3review0.17

Mining Operations · S3review0.17

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 51-8099	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)