A RevOps hire in 2026 can be paid $72,000 or $140,000 for work that lands on the same revenue team. Both numbers sit inside one function and one dataset — 2,211 US postings collected by Glozo Talent Intelligence over the first half of 2026. The single figure everyone will quote from it, a $112,000 median, is the least useful number in the whole file. What matters is the ladder underneath it: which rung a title lands on, and what moves you up one.
2,211
US postings analyzed
$112k
median, all roles
43.1%
disclose pay
21.8×
candidates per vacancy
8 days
average listing life
The ladder inside one function
Eight titles, one function, a 94% spread from bottom to top.
Median annual salary by role
USD · disclosed postings
Two things in that chart are worth more than the rest of the report.
The newest title pays the most. GTM Engineer leads at $140,000 — a title that did not meaningfully exist three years ago, sitting above marketing operations ($125,000) and above revenue operations proper ($120,000). Nothing about seniority explains this. It is a pricing signal on a skill mix, not on a career stage.
The floor is a title problem, not a tier problem. A CRM manager’s $72,000 median sits below the $97,079 that the specialist tier earns on average — two cuts of the same market that only reconcile if the title itself caps the price, regardless of how good the person is. Sales operations at $97,090 tells the same story from the middle: it is the classic RevOps job, and it is paid almost exactly the tier average while newer titles clear it by $23–43k.
If you are inside the function, the practical read is blunt: relabelling your work is worth more than another year of it.
The seniority curve, and the step that pays
Median annual salary by seniority tier
USD · disclosed postings · each riser is the jump to the next tier
Entry to leader is 2.8× across the range. But the steps are not evenly spaced, and the interesting one is the first: entry to specialist adds about 56%, the largest single jump on the ladder. Specialist to expert adds 26%; expert to leader adds 43%.
That shape says the function prices competence far more steeply than it prices tenure. The money is in getting out of the entry tier fast, not in accumulating years inside it.
What the market actually pays for
Salary uplift by skill
% vs the industry median
AI and automation carry a 47.3% premium — more than double the next band. Applied to the $112,000 function median, that is roughly $165,000 (our arithmetic, not a published figure).
Read the rest of the list as a gradient from building to operating. SQL, Python and API work pays +21%. BI tools +18%. Then certifications: marketing-automation +15%, Salesforce Admin +13.6%. Every step down that list is a step from making a system to running someone else’s system, and the market pays the difference. A Salesforce Admin certification is the single most common credential in this function and the least valuable one measured here.
One honest caveat before anyone builds a career plan on it: this is a premium measured on job postings, not a raise measured on people. It tells you what employers price into a req, not what your current employer will pay you for learning n8n.
Deep pool, fast market
The supply side looks comfortable and is not. There are 46,821 candidates in the pool and 21.8 candidates per open vacancy — and the average posting is live for 8 days.
Candidates per open vacancy
Those two facts belong to different markets. A 22:1 ratio describes the generalist middle. The 8-day clock describes what happens when a good req opens. The source splits it by role: GTM Engineer postings run longest at about 9 days, deal desk analyst roles clear fastest at about 6. So the harder-to-fill seat is the technical one, exactly as the pay ladder predicts.
Share of the candidate pool by seniority
% of 46,821 candidates
The pool is 55.7% specialist and 2.4% entry. RevOps is not a first job — people arrive from sales, marketing or analytics, which is the same conversion pattern we found on the practitioner side of the GTM Engineer title.
Note the inversion further up: 24.6% call themselves leaders against 17.3% experts. A pool with more leaders than experts is either a function that promotes to title early, or a self-reported seniority field doing what self-reported seniority fields do. The dataset cannot distinguish the two, and neither can we — but if you are hiring a “Head of RevOps”, assume the title is a weaker signal here than in engineering.
Geography: still the hubs
Median annual salary by state
USD
California leads at $143,500, about 9% above Washington ($132,000), with New York third ($129,000). Florida is lowest of the ranked states at $103,000 — a 39% gap from top to bottom, which is less than half the spread the title ladder produces.
Median annual salary by city
USD
San Francisco tops the cities at $150,000, then New York ($136,500) and Seattle ($134,500). These are web-sourced estimates with no posting count behind them, so they carry the weakest evidence in this report. Use them to sanity-check an offer, never to justify one.
Month to month: flat, not falling
Median posted pay by month
USD · rolling pooled median · H1 2026
The band runs from $105,000 (June) to $116,828 (April) among the months with enough disclosed salaries to stand alone — about 10%. Scaled from zero, those bars are the same length, and that flatness is the finding. Six months of data in a niche this size cannot support a trend claim, and the June dip to $105,000 is not evidence that RevOps pay is falling.
One discrepancy we could not resolve: the per-month posting counts sum to 2,038 against the 2,211 headline — about 8% of postings unaccounted for in the monthly table. The source does not explain the gap. It does not move any median here, but it is a reason to treat monthly counts as approximate.
The employment mix is the least ambiguous cut in the report: 91.0% full-time, 4.1% contract, and the remaining 4.9% split across internship, temporary and part-time. Employers are building RevOps in-house, not renting it.
Where this disagrees with our own GTM Engineer report
We published a GTM Engineer market report in July on a different, narrower Glozo dataset. It put the median at $150,000 across 71 disclosed postings over Jun 2025 – Jun 2026. This report puts GTM Engineer at $140,000 inside a RevOps basket over H1 2026.
We are not going to average them, and neither should you. Three differences generate the $10k, and each one is informative:
- Different populations. Ours was every posting carrying the standalone title. This one is GTM Engineer as a role classified inside a revenue-operations query — a classification that will pull in RevOps reqs with engineering duties bolted on, which pay less than a dedicated seat.
- Different windows. Ours spans thirteen months including the pre-spike 2025 baseline; this one is six months of 2026.
- Different denominators. 71 disclosed postings against an unpublished per-role count. At these sample sizes a $10k gap is inside the noise either way.
The agreement matters more than the gap. Two independently framed cuts of the US market both put GTM Engineer at the top of the revenue-operations pay ladder, and both put AI and automation skill at the centre of why. A $140–150k band for the title is the honest way to state it.
A third instrument has landed since, and it agrees on the ranking. RevOps vs GTM Engineer vs Analytics Engineer reads 155 US postings from a single week of LinkedIn — a sample built so the three seats are directly comparable — and puts RevOps Manager at $145,450 against GTM Engineer at $160,000. Same order, third method; the gap between the seats is what moves, not which one leads.
What to do with this
If you are hiring. Price the seat by title-and-skill, not by the function median — posting a “RevOps Manager” req at $112,000 and expecting AI automation work in the job description is a $50k mismatch you will discover eight days too late. Budget the technical seat against the $140,000 rung. And do not read 21.8 candidates per vacancy as leverage: it is a generalist number, and the specialist seat you actually want stays open longest.
If you are in the function. The two levers this data supports are the same lever twice: move up the title ladder, and acquire the build skills that justify it. AI and automation at +47.3% is the only premium in this dataset large enough to outrun a title change. Another Salesforce certification is worth +13.6%, and the market has priced that fact for years.
If you are early. The entry tier is 2.4% of the pool and pays $62,400. That is a thin, badly paid door into a well-paid function. The people inside it overwhelmingly came in sideways from sales, marketing or analytics — which remains the cheaper route in.
Methodology & source
This report is published by RevGuild and analyzes data collected and published by a third party. Publisher and data collector are distinct, and the distinction matters more than usual here: we did not collect this data and have no access to the underlying postings.
Data: the USA Revenue Operations Salary Report 2026 by Elvina Drozdova, Data Scientist at Glozo, published 15 July 2026 and accessed 12 August 2026. Every figure quoted above is transcribed from that report’s own published data tables into src/data/research/us-revenue-operations-salary-2026.json, committed with this post. The analysis, the framing, the cross-read against our own dataset and every judgement in this post are ours; the numbers are theirs. Where we compute something the source did not publish — the step sizes on the seniority curve, the $165,000 AI-premium figure, the 2,038-vs-2,211 posting gap — we say so inline.
Base population: 2,211 analyzed US job postings; 43.1% disclosed a pay range. Every salary figure rests on that disclosed subset, not on all 2,211. All pay is annual salary in USD as disclosed in postings.
Caveats carried over from the source, unchanged:
- No per-role n. The role ladder publishes no posting count per title. The ordering is directional; a $5k difference between adjacent rungs means nothing.
- No per-area n. State and city figures are web-sourced estimates, not posting-level medians. They are the weakest evidence here.
- Suppressed months. January (n=46) and May (n=122) rest on too few disclosed salaries to stand alone and are marked with an asterisk in the chart. The monthly series is a rolling pooled median.
- The cuts are independent. Role, seniority, state and skill are four separate lookups over the same population, not a cross-tab. An expert-tier GTM Engineer in California is not $140,000 × the California ratio × the expert ratio. Never multiply them.
- Candidate-pool tiers are self-reported and come from the supply side (46,821 profiles), not from the postings.
One benchmark in the source is not posting data at all. Its gender-pay section comes from the US Bureau of Labor Statistics and covers the broad business-operations-specialists occupation group rather than revenue operations: women’s median earnings $81,796 against men’s $99,788, a gap of about 18%, modestly narrower than the roughly 19% national gap across all occupations in the same release. We reproduce it with the source’s own framing — a directional proxy, because RevOps is not a standalone BLS category — and we did not independently verify it against BLS.
Corrections. If a figure here misrepresents the source, tell us and we will fix the post and say what changed.