I Built a Tool to Compare Senior Engineer Salaries Across 17 Cities, and I Want Your Take

I just shipped something I have wanted to exist for a long time, and I would genuinely love your opinion on it.

It is an interactive dashboard that compares senior software engineer compensation across 17 cities, from 2016 all the way out to a forecast for 2035. You can play with it here: hub.gazar.dev/swe-salaries. Open it in another tab, have a click around, and then come back and tell me what you think. This article is me explaining what I built and why, and then asking for your honest read on it.

Why I built it

Every time an engineer asks me "should I move to city X for the money?" the honest answer is "it depends, and the headline number is lying to you."

Headline total compensation is the figure everyone quotes and the worst one to make a decision on. A 300k offer in San Francisco and a 120k offer in Lisbon are not what they look like once you run them through tax, cost of living, and what you can actually save. The number that matters is never the gross. It is what you keep, what it buys, and what is left over at the end of the month. I have watched plenty of engineers make this move, and the gap between the offer letter and the lived reality is enormous.

So I built the thing I wished I had when I was making those decisions.

The four lenses

The core idea is that you should never look at compensation through one number. The tool shows the same salary through four different lenses, and the ranking changes dramatically depending on which one you pick:

• Gross headline total comp: base, bonus, and equity. The number recruiters quote.
• Take-home after tax: what actually lands in your account once taxes and social security are taken out.
• Purchasing power: that take-home adjusted to what it would buy in NYC terms, so you can compare cities honestly.
• Saving power: the investable surplus left after you have actually lived. This is the one almost nobody calculates, and it is the one that decides whether you build wealth or just earn a big number.

Watching a city climb to the top on gross and then fall to the bottom on saving power is the entire point. That reordering is the lesson.

You can filter by region, toggle linear or logarithmic scales, and switch between the four metrics to see how the rankings shuffle. This is the same trade-off thinking I push in understanding the job market: the right move depends entirely on what you are optimising for.

I did not stop at salary

Salary is only one input into a much bigger life decision, so the dashboard goes further than pay.

There is an investment comparison tab that takes 100k invested at the end of 2015 across stocks, crypto, gold, and leveraged property, and shows where you would have landed by the end of 2025. There is a property leverage module that models the 10:1 game most people are actually playing without naming it: a 100k deposit on a 1M home with an interest-only mortgage, and what that does over time. And there is a personal planning scenario, a worked example of someone investing 1,000 a month, walking through the priority order I actually believe in: emergency fund, then employer pension match, then a tax-advantaged investment account, then the property question.

If you have read The Psychology of Money, none of the principles underneath will surprise you. The tool is really an attempt to make those principles concrete for our specific situation as engineers choosing where to work.

How I forecast to 2035

The part I want the most scrutiny on is the forecast, because forecasting is where these tools usually go wrong.

I deliberately did not just draw a line through the historical data and extend it. The 2026 to 2035 projections combine published salary-budget growth rates (Mercer, WorldatWork, Robert Walters), long-run inflation expectations from the central banks (the Fed, ECB, Bank of England, RBA), and currency forecasts from major institutions. Iran is modelled as a deliberate cautionary exception, with hyperinflation in the 30 to 40 percent range, because I wanted at least one case that shows what currency collapse does to a salary that looks fine in local terms.

The underlying data through 2025 comes from Levels.fyi, Glassdoor, Numbeo, PwC, the IMF, and others, all listed in the tool. It is a model, which means it is wrong in some specific way I cannot see yet, and that is exactly why I am publishing it and asking.

This is where you come in

I am putting this out as a draft of an idea, not a finished verdict, and I want your honest reaction.

A few things I am genuinely unsure about and would love your comment on:

• Is the saving-power lens the right one to lead with, or is there a better single metric for "this is the offer that actually makes you wealthier"?
• Which city or region did I get wrong? If you live somewhere on this list, do the numbers match your lived reality or are they off?
• What did I miss entirely? Healthcare, childcare, visa and residency friction, equity that never vests, the cost of moving back. The soft stuff that wrecks the spreadsheet.
• Does the forecast feel defensible, or have I been too optimistic or too cautious somewhere?

So please, give it a go, and then tell me where I am wrong. The model gets better with every engineer who pokes a hole in it, and I would rather hear the hard feedback now than ship a confident wrong answer.

If you find this useful, I write about engineering careers, the senior-to-staff path, and the decisions that actually move the needle every week in Monday BY Gazar on Substack, and I break things down on video on Gazar Breakpoint on YouTube.

And if you are weighing a specific move or offer right now, book a free intro call and we can talk it through against your real numbers.