Geographic discounting meets leveling: compensating different levels of seniority based on location

Pave Data Lab
•
December 1, 2021
•
4
min read
•

We’ve previously discussed how compensation for entry-level software engineers has remained geographically dependent even as more companies adopt remote and hybrid models. 

But what about for more senior level roles? Should you budget for the same market discount for hires across multiple levels of expertise? 

This time, we took a deep dive into our data to see how geographical discounts change for software engineers across the United States depending on their level of seniority. Spoiler: they change quite a bit. 

A look at the data

We looked at thousands of software engineer salaries from technology companies in Tier 1 cities like San Francisco, New York City, Los Angeles, and Seattle versus Tier 3 cities to understand the salary discount at various levels.

The largest discount, we found, is for entry level individual contributors (P1 and P2 in our leveling system), at 11% each. New hires and early career professionals continue to benefit from working in the major tech markets.

For more senior hires, geographic discounting quickly fades away. 

Highly tenured engineers, with common job titles like Principal Engineer and Staff Engineer, are only paid a 3% difference between these market tiers.

What this means for hiring

This data aligns with how our companies anecdotally have been thinking about geographic compensation. 

As employees become more senior, employers are more likely to factor their experience and skill set into their compensation package than their geographical location. 

More senior candidates are also in shorter supply, so they have more leverage in the hiring and compensation conversation. 

It’s worth noting that we looked at geographical discounts for individual contributor roles this time around. 

This script flips for manager and executive compensation where the responsibility of team building is much more effectively executed when co-located with pockets of talent, which continue to group in major metropolitan areas.

How geographical discounts have changed over time

The world of work looks quite different now than it did even a year ago.

In a future post, we’ll cover how geographical discounts looked before, during, and after the pandemic.

Learn more about Pave’s end-to-end compensation platform
Pave Data Lab
The Pave Data Lab
The only data-driven blog powered by real-time HRIS & Equity integrations.

Become a compensation expert with the latest insights powered by Pave.

(function (h, o, t, j, a, r) { h.hj = h.hj || function () { (h.hj.q = h.hj.q || []).push(arguments) }; h._hjSettings = { hjid: 2412860, hjsv: 6 }; a = o.getElementsByTagName('head')[0]; r = o.createElement('script'); r.async = 1; r.src = t + h._hjSettings.hjid + j + h._hjSettings.hjsv; a.appendChild(r); })(window, document, 'https://static.hotjar.com/c/hotjar-', '.js?sv='); !function () { var analytics = window.analytics = window.analytics || []; if (!analytics.initialize) if (analytics.invoked) window.console && console.error && console.error("Segment snippet included twice."); else { analytics.invoked = !0; analytics.methods = ["trackSubmit", "trackClick", "trackLink", "trackForm", "pageview", "identify", "reset", "group", "track", "ready", "alias", "debug", "page", "once", "off", "on", "addSourceMiddleware", "addIntegrationMiddleware", "setAnonymousId", "addDestinationMiddleware"]; analytics.factory = function (e) { return function () { var t = Array.prototype.slice.call(arguments); t.unshift(e); analytics.push(t); return analytics } }; for (var e = 0; e < analytics.methods.length; e++) { var key = analytics.methods[e]; analytics[key] = analytics.factory(key) } analytics.load = function (key, e) { var t = document.createElement("script"); t.type = "text/javascript"; t.async = !0; t.src = "https://cdn.segment.com/analytics.js/v1/" + key + "/analytics.min.js"; var n = document.getElementsByTagName("script")[0]; n.parentNode.insertBefore(t, n); analytics._loadOptions = e }; analytics.SNIPPET_VERSION = "4.13.1"; analytics.load("0KGQyN5tZ344emH53H3kxq9XcOO1bKKw"); analytics.page(); } }(); $(document).ready(function () { $('[data-analytics]').on('click', function (e) { var properties var event = $(this).attr('data-analytics') $.each(this.attributes, function (_, attribute) { if (attribute.name.startsWith('data-property-')) { if (!properties) properties = {} var property = attribute.name.split('data-property-')[1] properties[property] = attribute.value } }) analytics.track(event, properties) }) }); var isMobile = /iPhone|iPad|iPod|Android/i.test(navigator.userAgent); if (isMobile) { var dropdown = document.querySelectorAll('.navbar__dropdown'); for (var i = 0; i < dropdown.length; i++) { dropdown[i].addEventListener('click', function(e) { e.stopPropagation(); this.classList.toggle('w--open'); }); } }