Salary Benchmarks

The benchmarks at /benchmarks turn the salary data we extract from job postings into compensation matrices — tables that show what a role pays once you slice it by level, city, and tech stack. Instead of a single national average, you can see how pay shifts as you move from a junior to a staff level, from one metro to another, or across the stacks a role tends to hire for.

What a matrix shows

Each cell is anchored on observed postings, so the numbers reflect what employers are actually offering rather than self-reported figures. Read a matrix the way you'd read any pivot table: pick the dimension you care about along each axis and the cell tells you the typical pay for that combination. We surface percentile anchors (not just a mean) so you can see the spread, and every figure traces back to the same extraction pipeline described in our methodology.

Free vs. Pro

Everyone can see the base matrix— the headline breakdown that answers “what does this pay, roughly, and how does it move across the top levels and metros?” That much is free.

Prounlocks the deep filters: drill into finer level bands, narrow to a specific city, and intersect with an individual tech stack so you can answer questions like “what does a senior backend engineer working in Go make in Austin?” The deeper level, city, and stack cuts are where the matrices become a negotiation tool rather than a ballpark.

Where the numbers come from

Benchmarks are derived from the same job-posting corpus that powers the rest of HiringTrends and are refreshed as new postings land. For the full story on how we parse salary ranges, normalize levels, and handle missing data, see the methodology page.