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Key statistics

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

4 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

Provides advanced technical and analytical support across major energy business lines such as exploration, production, gas, power, and offshore operations. At the Lead Support Specialist (S4) level, the role owns team process and quality, cross-case patterns and process gaps, and drives team-level quality and efficiency. Mentors and coordinates the support team.

What this level does

Adapt data-management and normalization procedures when a property or contract presents an unprecedented situation (e.g. new meter configuration, non-standard billing structure) that the standard workflow does not cover
Resolve conflicts in customer data flow spanning CIS/Billing, EDI, and settlements, determining the method to correct root-cause errors that ripple across systems
Serve as working lead for a group of support analysts on the annual utility budget build, distributing tasks, reviewing outputs, and coaching on procedure
Coordinate with utility companies to reconcile disputed usage and explore incentive-program documentation requirements, negotiating corrections outside routine channels
Prepare non-routine operational data packages for senior leadership, resourcefully assembling figures across disparate energy and billing systems

Knowledge applied: Extensive knowledge of energy operations procedures and their administration, enough to adapt them for unprecedented meter, contract, or cross-system situations.
Complexity & problem solving: Understands the downstream implications of data errors across CIS/Billing, EDI, and settlements; recommends new solutions and determines methods for new assignments.
Collaboration & interaction: May informally guide and coach less experienced analysts as a working lead; negotiates corrections with utility companies.
Typical experience: 4–6 years; advanced support experience.

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$92k

San Francisco-Oakland-Fremont, CA$82k

Washington-Arlington-Alexandria, DC-VA-MD-WV$76k

Boulder, CO$75k

Seattle-Tacoma-Bellevue, WA$75k

Boston-Cambridge-Newton, MA-NH$72k

Lexington Park, MD$70k

Trenton-Princeton, NJ$70k

Pay only — metro-level demand isn't in public data (it needs job postings). National median $55k; 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 S4 (S4 — Lead Support Specialist) from the levels around it — this level only. Every word is real canon for this profile.

Scope: Team process and quality
Autonomy: Works independently; owns improvements
Complexity: Cross-case patterns and process gaps
Impact: Team-level quality and efficiency
Decision rights: Owns process and quality decisions for the team
Leadership: Mentors and coordinates the support team

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

Promotion

The next rung from S4 is S5.

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
President & Chief Executive Officer, Energy Operations	jf_energy_operations::E4	$389,207†	confident0.06
Senior Manager, Energy Operations	jf_energy_operations::M4	$167,689†	confident0.06
Senior Energy Operations Engineer	jf_energy_operations::P4	$109,466†	confident0.06
Senior Energy Operations Technician	jf_energy_operations::S3	$49,566†	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

S4

jf_energy_operations::S4

Advanced Energy Operations Analyst

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: 4 / 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 · S4review0.17

Control Operations · S4review0.17

Emissions · S4review0.17

Energy Grid · S4review0.17

Land / Property · S4review0.17

Mining Operations · S4review0.17

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)