📈 IT salary movement
What is being advertised right now? We record the salary ranges PUBLISHED in job ads every day and show how they move. Every figure comes with its sample size.
Hungary
1 708 252
Range midpoint · gross HUF/month
1 397 030 – 2 041 734
n = 64
· 7.9% publishes pay
daily ▲0.5%
weekly ▼13.5%
monthly ▼13.5%
yearly ·
Europe
2 412 533
Range midpoint · gross HUF/month
2 075 417 – 2 808 866
n = 3 988
· 13.1% publishes pay
daily ▼0.6%
weekly ▲8.1%
monthly ▲3.9%
yearly ·
North America
5 115 791
Range midpoint · gross HUF/month
4 365 576 – 6 057 237
n = 13 489
· 68.0% publishes pay
daily ±0
weekly ±0
monthly ±0
yearly ·
All
4 572 404
Range midpoint · gross HUF/month
3 885 363 – 5 456 970
n = 18 608
· 28.1% publishes pay
daily ▼1.1%
weekly ▲1.5%
monthly ▲1.5%
yearly ·
Measuring since: 2026-07-26 · Last measured: 2026-10-09 · 76 days recorded · 99.8% of our salary data is not quoted in forint, so the forint figure also moves with the exchange rate. Base rate fixed on: 2026-07-26 · Currency effect since base: +2.64%
⏱️ Measurable time windows
We only report movement when there is something to compare against. For windows not yet available we state the date — we never fill the gap with an estimate.
daily
1 days
✓ available
weekly
7 days
✓ available
monthly
30 days
✓ available
yearly
365 days
available from: 2027-07-26
290 days to go
How the median moved · All · gross HUF/month
4 887 083
07-2608-0408-1308-2208-3109-0909-1809-2710-0610-09
🎯 Where do you stand?
Enter your gross monthly pay and we show what share of advertised ranges you sit above. The amount never leaves your browser — the maths runs on your device; we neither see nor store it.
ℹ️ Approximate: we compare against the MIDPOINT of advertised ranges, not actually paid salaries. Bonus, equity and benefits are not included.
🌱 Fresh ads vs full stock
Pay levels in newly posted roles move before the long-standing stock — hence a leading indicator. A cross-sectional comparison within today's live stock.
Full live stock
4 692 994
n = 18 608
Last 7 days
3 956 303
-15.7%
vs the stock · n = 2 880
Last 30 days
4 268 715
-9.0%
vs the stock · n = 7 429
🪜 By level
The career ladder: how much more the next step pays. Bars show the ratio of medians.
Intern
2 619 346
n=212
Junior
2 632 988
+1%
vs previous
n=136
Medior
3 503 784
+33%
vs previous
n=190
Senior
4 638 425
+32%
vs previous
n=6 273
Lead
4 911 273
+6%
vs previous
n=697
Architect
5 047 697
+3%
vs previous
n=414
Principal
6 188 204
+23%
vs previous
n=2 775
| Level | Range midpoint | Difference | Range floors – Range ceilings | Range width | Full field (p10–p90) | daily | weekly | monthly | yearly | sample |
|---|---|---|---|---|---|---|---|---|---|---|
| Principal | 6 024 905 | +28% | 5 184 122 – 7 270 052 | +40% | 4 255 345 – 8 601 276 | ▲0.4% | ▼0.7% | ▲0.3% | · | 2 775 |
| Architect | 4 903 738 | +4% | 4 092 728 – 5 866 243 | +43% | 2 680 704 – 6 952 180 | ▲0.5% | ▲5.4% | ▲2.8% | · | 414 |
| Lead | 4 771 205 | +2% | 4 092 728 – 5 729 819 | +40% | 2 441 667 – 7 370 167 | ±0 | ▲2.9% | ▲2.9% | · | 697 |
| Senior | 4 506 138 | -4% | 3 847 164 – 5 402 400 | +40% | 2 158 982 – 6 616 576 | ±0 | ±0 | ±0 | · | 6 273 |
| Medior | 3 403 857 | -27% | 2 714 160 – 4 113 191 | +52% | 2 210 520 – 5 622 862 | ±0 | ±0 | ▲2.7% | · | 190 |
| director | 3 332 147 | -29% | 2 975 680 – 3 723 542 | +25% | 2 198 864 – 6 311 511 | · | ▲5.5% | · | · | 20 |
| Junior | 2 557 896 | -45% | 2 182 788 – 3 069 546 | +41% | 1 106 380 – 4 414 274 | ▲1.6% | ▲23.3% | ▲12.9% | · | 136 |
| Intern | 2 552 570 | -46% | 2 269 827 – 2 859 507 | +26% | 512 750 – 4 059 986 | ±0 | ▲0.3% | ▲5.3% | · | 212 |
| mid-level | 2 103 428 | -55% | 1 781 155 – 2 441 667 | +37% | 993 049 – 4 452 888 | ▲1.1% | ▼3.0% | ▼2.2% | · | 399 |
| manager | 1 988 002 | -58% | 818 546 – 3 001 334 | +267% | 1 346 156 – 4 107 978 | ▼5.8% | ▼29.6% | ▼33.6% | · | 123 |
| entry-level | 1 206 267 | -74% | 1 113 400 – 1 423 742 | +28% | 562 536 – 2 477 901 | ▲7.1% | ▼17.7% | ▼25.9% | · | 57 |
⚙️ By technology
Median per technology against the overall median — where the premium is.
| Technology | Range midpoint | Difference | Range floors – Range ceilings | Range width | Full field (p10–p90) | daily | weekly | monthly | yearly | sample |
|---|---|---|---|---|---|---|---|---|---|---|
| Rust | 5 592 912 | +19% | 4 772 530 – 6 821 213 | +43% | 3 336 826 – 9 140 425 | ▼0.7% | ▼1.1% | ▲0.7% | · | 1 009 |
| Spark | 5 433 872 | +16% | 4 529 285 – 6 562 006 | +45% | 2 550 861 – 7 530 619 | ±0 | ▼1.2% | ▼1.3% | · | 1 010 |
| AI/ML | 5 301 338 | +13% | 4 502 000 – 6 275 516 | +39% | 2 743 197 – 8 112 877 | ±0 | ±0 | ±0 | · | 3 800 |
| LLM | 5 301 338 | +13% | 4 502 000 – 6 279 512 | +39% | 2 652 108 – 8 294 867 | ±0 | ±0 | ±0 | · | 2 958 |
| C/C++ | 5 115 791 | +9% | 4 365 576 – 6 139 091 | +41% | 3 053 830 – 7 653 400 | ±0 | ±0 | ±0 | · | 2 202 |
| Go | 4 985 909 | +6% | 4 174 582 – 5 972 654 | +43% | 2 406 568 – 7 204 565 | ±0 | ±0 | ▲2.3% | · | 881 |
| Kubernetes | 4 970 005 | +6% | 4 092 728 – 6 002 667 | +47% | 2 211 327 – 7 503 334 | ▼0.3% | ▲1.1% | ▲2.5% | · | 2 972 |
| TypeScript | 4 970 005 | +6% | 4 189 006 – 5 866 243 | +40% | 2 284 196 – 7 503 334 | ▼0.6% | ±0 | ▲2.3% | · | 2 291 |
| GCP | 4 903 738 | +4% | 4 092 728 – 5 831 796 | +42% | 2 150 611 – 7 234 578 | ±0 | ±0 | ▲3.1% | · | 2 298 |
| data science | 4 850 725 | +3% | 4 098 184 – 5 811 673 | +42% | 2 315 159 – 7 650 672 | ▼0.4% | ▲0.3% | ▼1.1% | · | 1 543 |
| Python | 4 813 363 | +3% | 4 056 575 – 5 729 819 | +41% | 2 319 212 – 7 489 691 | ▼0.5% | ±0 | ▲2.0% | · | 7 211 |
| AWS | 4 771 205 | +2% | 3 956 303 – 5 702 534 | +44% | 2 193 451 – 7 094 061 | ±0 | ±0 | ▲3.0% | · | 3 973 |
| React | 4 781 370 | +2% | 4 092 728 – 5 647 964 | +38% | 2 095 561 – 7 162 273 | ▼1.2% | ±0 | ±0 | · | 1 892 |
| Terraform | 4 771 205 | +2% | 3 939 932 – 5 626 136 | +43% | 2 186 881 – 7 111 523 | ±0 | ▲0.6% | ▲2.9% | · | 1 571 |
| PostgreSQL | 4 555 175 | -3% | 3 668 272 – 5 456 970 | +49% | 2 011 531 – 6 889 425 | ▼1.8% | ▲1.1% | ▲1.1% | · | 1 035 |
| Azure | 4 506 138 | -4% | 3 816 305 – 5 456 970 | +43% | 1 909 462 – 7 069 548 | ±0 | ▲2.1% | ▲4.2% | · | 2 370 |
| Linux | 4 466 378 | -5% | 3 667 084 – 5 320 546 | +45% | 2 102 604 – 6 984 922 | ▼0.7% | ▲6.9% | ▲7.1% | · | 1 874 |
| C# | 4 466 378 | -5% | 3 677 998 – 5 385 347 | +46% | 2 136 458 – 7 212 277 | ▼0.4% | ▲5.3% | ▲8.0% | · | 912 |
| Java | 4 439 871 | -5% | 3 683 455 – 5 456 970 | +48% | 2 049 609 – 6 914 675 | ±0 | ±0 | ▲0.9% | · | 2 218 |
| JavaScript | 4 241 071 | -10% | 3 658 974 – 5 044 969 | +38% | 1 964 509 – 6 606 071 | ±0 | ▲1.5% | ▲3.2% | · | 1 578 |
| GitHub | 4 239 568 | -10% | 3 667 084 – 5 020 412 | +37% | 2 099 986 – 6 519 033 | ±0 | ▲1.3% | ▲3.2% | · | 1 313 |
| Docker | 4 181 431 | -11% | 3 547 031 – 5 044 969 | +42% | 1 847 426 – 6 548 364 | ▼0.9% | ▲2.5% | ▲3.7% | · | 1 525 |
| SQL | 4 185 407 | -11% | 3 601 600 – 4 965 843 | +38% | 1 858 162 – 6 821 213 | ▼0.7% | ▲0.8% | ▲1.3% | · | 2 827 |
| Git | 3 710 937 | -21% | 3 189 599 – 4 480 172 | +40% | 1 508 950 – 5 735 636 | ▼1.8% | ▲4.9% | ▲8.0% | · | 1 095 |
🧩 By role
Median per role against the overall median.
| Role | Range midpoint | Difference | Range floors – Range ceilings | Range width | Full field (p10–p90) | daily | weekly | monthly | yearly | sample |
|---|---|---|---|---|---|---|---|---|---|---|
| Engineering Manager | 6 345 702 | +35% | 5 456 970 – 7 474 303 | +37% | 3 375 604 – 9 227 736 | ±0 | ▼0.8% | ▼1.1% | · | 484 |
| AI / ML Engineer | 5 595 563 | +19% | 4 804 862 – 6 821 213 | +42% | 2 788 539 – 8 185 455 | ±0 | ▲0.5% | ▲3.0% | · | 660 |
| Product Manager | 5 168 805 | +10% | 4 502 000 – 6 139 091 | +36% | 2 947 767 – 7 486 963 | ▼0.8% | ▼2.0% | ±0 | · | 426 |
| Software Engineer | 5 145 744 | +10% | 4 365 576 – 6 139 091 | +41% | 2 488 905 – 7 912 607 | ▼0.4% | ▲0.6% | ▲0.8% | · | 4 400 |
| Data Scientist | 5 092 717 | +9% | 4 365 576 – 5 948 097 | +36% | 2 521 917 – 8 009 413 | ▼0.5% | ▲3.9% | · | · | 355 |
| Solution / Enterprise Architect | 4 981 555 | +6% | 4 095 456 – 5 959 011 | +46% | 2 594 964 – 6 756 542 | ±0 | ▲1.6% | ±0 | · | 381 |
| Project Manager | 4 913 997 | +5% | 4 283 721 – 6 002 667 | +40% | 2 749 282 – 7 234 578 | ▼2.0% | ▲1.0% | ±0 | · | 448 |
| Security Engineer | 4 744 698 | +1% | 3 983 588 – 5 684 335 | +43% | 2 136 458 – 7 293 240 | ±0 | ▲3.3% | ▲5.3% | · | 641 |
| Architect | 4 715 540 | 0% | 3 956 303 – 5 647 964 | +43% | 2 588 949 – 7 162 273 | ±0 | ▲5.7% | · | · | 341 |
| Other | 4 235 769 | -10% | 3 547 031 – 5 102 267 | +44% | 1 801 745 – 7 109 068 | ▼1.4% | ▲2.1% | ▼1.7% | · | 5 677 |
| IT Consultant | 4 231 688 | -10% | 3 653 496 – 5 231 875 | +43% | 1 973 734 – 6 545 636 | ▼0.5% | ±0 | ▼2.3% | · | 922 |
| Data Engineer | 3 976 004 | -15% | 3 410 606 – 4 605 683 | +35% | 1 624 685 – 6 986 286 | ▼1.1% | ▲4.7% | ▲1.7% | · | 414 |
| Fullstack Developer | 3 660 574 | -22% | 3 052 629 – 4 385 664 | +44% | 1 625 787 – 6 375 596 | ±0 | ▲4.1% | ▲0.6% | · | 370 |
| QA / Test Engineer | 3 525 390 | -25% | 3 055 903 – 4 100 913 | +34% | 1 554 108 – 5 388 758 | ▼1.5% | ▲1.5% | ▲8.6% | · | 434 |
🏠 By work location
Remote or on-site — the difference in advertised ranges.
| By work location | Range midpoint | Difference | Range floors – Range ceilings | Range width | Full field (p10–p90) | daily | weekly | monthly | yearly | sample |
|---|---|---|---|---|---|---|---|---|---|---|
| Hybrid | 5 250 147 | +12% | 4 365 576 – 6 316 388 | +45% | 2 289 063 – 8 008 786 | ±0 | ▲9.0% | ▲7.1% | · | 1 981 |
| On-site | 4 572 404 | -3% | 3 855 349 – 5 516 997 | +43% | 2 027 982 – 7 472 775 | ±0 | ▲1.5% | ▲1.5% | · | 11 550 |
| Remote | 4 241 071 | -10% | 3 667 084 – 5 042 240 | +37% | 1 831 250 – 7 106 339 | ▼2.3% | ▼3.6% | ▼2.0% | · | 5 077 |
🔓 Pay transparency
What share of ads publish a salary range at all. Our most reliable trend indicator: a ratio, so neither exchange rates nor sample mix can move it.
US
69.4%
12 793 / 18 424
SK
68.1%
124 / 182
LT
64.0%
103 / 161
EE
50.0%
57 / 114
CA
49.5%
696 / 1 406
AT
28.7%
137 / 477
IT
27.2%
152 / 559
EU
25.2%
1 132 / 4 497
IE
16.4%
159 / 967
PL
16.3%
448 / 2 750
GB
14.5%
800 / 5 503
NL
11.8%
155 / 1 315
PT
11.3%
143 / 1 263
DE
11.1%
599 / 5 397
ES
10.8%
227 / 2 102
CH
10.4%
43 / 412
HU
7.9%
64 / 810
FR
7.5%
219 / 2 923
SE
1.0%
42 / 4 263
| Country | Publishes pay | With pay | Total ads | Range midpoint | daily | weekly | monthly | yearly |
|---|---|---|---|---|---|---|---|---|
| US | 69.4% | 12 793 | 18 424 | 5 142 298 | ▼0.12pp | ±0 | ▼1.05pp | · |
| SK | 68.1% | 124 | 182 | 1 315 690 | ▲0.91pp | ▲3.69pp | ▲8.01pp | · |
| LT | 64.0% | 103 | 161 | 1 899 870 | ▲0.45pp | ▼0.73pp | ▼2.69pp | · |
| EE | 50.0% | 57 | 114 | 2 026 528 | ▼1.33pp | ▼1.58pp | ±0 | · |
| CA | 49.5% | 696 | 1 406 | 4 075 404 | ▼0.43pp | ▲1.66pp | ▲1.2pp | · |
| AT | 28.7% | 137 | 477 | 2 110 967 | ▲0.63pp | ▲0.13pp | ▼7.27pp | · |
| IT | 27.2% | 152 | 559 | 1 438 473 | ▲1.17pp | ▲3.36pp | ▲0.91pp | · |
| EU | 25.2% | 1 132 | 4 497 | 4 401 138 | ▲0.22pp | ▲1.17pp | ▲1.51pp | · |
| IE | 16.4% | 159 | 967 | 3 091 058 | ▲0.4pp | ▲1.57pp | ▼0.87pp | · |
| PL | 16.3% | 448 | 2 750 | 2 012 542 | ▲0.26pp | ±0 | ▼0.15pp | · |
| GB | 14.5% | 800 | 5 503 | 3 505 234 | ▲1.26pp | ▼0.13pp | ▼0.79pp | · |
| NL | 11.8% | 155 | 1 315 | 2 110 967 | ▲0.16pp | ▲0.81pp | ▼0.13pp | · |
| PT | 11.3% | 143 | 1 263 | 1 884 792 | ▲0.14pp | ▼0.08pp | ▲0.17pp | · |
| DE | 11.1% | 599 | 5 397 | 2 457 768 | ±0 | ▲0.06pp | ▼1.87pp | · |
| ES | 10.8% | 227 | 2 102 | 2 337 142 | ▲0.65pp | ▲1.06pp | ▼2.37pp | · |
| CH | 10.4% | 43 | 412 | 2 601 863 | ▲1.03pp | ▲0.72pp | ▼1.81pp | · |
| HU | 7.9% | 64 | 810 | 1 708 252 | ▲0.65pp | ▲1.45pp | ▲1.38pp | · |
| FR | 7.5% | 219 | 2 923 | 1 809 400 | ▲0.22pp | ▲0.19pp | ▼0.54pp | · |
| SE | 1.0% | 42 | 4 263 | 2 595 742 | ▲0.06pp | ▲0.42pp | ▲0.21pp | · |
⚖️ The EU pay transparency directive must be transposed by mid-2026; it requires the pay range to be disclosed up front in hiring. This table shows, day by day, where practice actually stands.
Barely more than 5% of Hungarian ads currently publish a range — among the lowest of the countries we measure.
🏢 Pay by company
Which company advertises what — employers publishing the most salary ranges.
| Pay by company | Range midpoint | sample | open roles | |
|---|---|---|---|---|
| Anthropic | 9 841 567 | 303 | 336 | Open → |
| Polymarket | 9 162 838 | 30 | 30 | Open → |
| Perplexity | 8 484 109 | 46 | 67 | Open → |
| SpaceXAI | 8 416 237 | 68 | 130 | Open → |
| OpenAI | 8 348 364 | 388 | 471 | Open → |
| Twenty | 8 131 170 | 24 | 25 | Open → |
| Wayve | 7 975 063 | 39 | 263 | Open → |
| Hightouch | 7 873 254 | 33 | 40 | Open → |
| G2i | 7 818 955 | 16 | 37 | Open → |
| Sierra | 7 737 508 | 49 | 59 | Open → |
📒 Measurement log
Raw figures for every measurement day, dated — so anyone can check what we claim above.
| Date | p10 | p25 | Median | p75 | p90 | Range floors | Range ceilings | Publishes pay | sample |
|---|---|---|---|---|---|---|---|---|---|
| 2026-10-09 | 1 981 919 | 3 246 856 | 4 692 994 | 6 057 237 | 7 486 963 | 3 885 363 | 5 456 970 | 28.1% | 18 608 |
| 2026-10-08 | 1 995 026 | 3 281 292 | 4 752 659 | 6 070 390 | 7 505 955 | 3 915 675 | 5 468 820 | 28.0% | 18 343 |
| 2026-10-07 | 1 992 645 | 3 238 530 | 4 662 134 | 5 991 281 | 7 408 137 | 3 859 248 | 5 397 550 | 27.9% | 18 557 |
| 2026-10-06 | 1 857 390 | 2 935 998 | 4 630 784 | 6 018 386 | 7 386 201 | 3 806 629 | 5 353 986 | 25.9% | 19 755 |
| 2026-10-05 | 1 867 086 | 2 973 722 | 4 659 288 | 6 029 667 | 7 403 882 | 3 837 061 | 5 404 623 | 26.3% | 19 805 |
| 2026-10-04 | 1 861 283 | 2 945 826 | 4 630 129 | 6 002 259 | 7 400 045 | 3 798 908 | 5 345 848 | 25.4% | 19 463 |
| 2026-10-03 | 1 845 900 | 2 907 293 | 4 659 288 | 6 030 215 | 7 443 508 | 3 824 727 | 5 373 529 | 24.0% | 18 557 |
| 2026-10-02 | 1 835 900 | 2 911 419 | 4 604 104 | 5 978 578 | 7 389 926 | 3 791 615 | 5 362 427 | 24.8% | 17 953 |
| 2026-10-01 | 1 854 381 | 2 999 698 | 4 568 766 | 5 966 270 | 7 374 525 | 3 762 513 | 5 375 018 | 24.7% | 17 661 |
| 2026-09-30 | 1 908 229 | 3 163 724 | 4 638 232 | 5 969 203 | 7 394 283 | 3 845 027 | 5 377 660 | 26.4% | 17 388 |
| 2026-09-29 | 1 911 894 | 3 135 646 | 4 611 066 | 5 968 844 | 7 380 395 | 3 791 022 | 5 377 337 | 26.6% | 17 615 |
| 2026-09-28 | 1 902 378 | 3 107 267 | 4 568 804 | 5 926 231 | 7 327 704 | 3 762 411 | 5 338 947 | 27.0% | 17 934 |
| 2026-09-27 | 1 887 280 | 3 082 944 | 4 566 067 | 5 926 231 | 7 307 683 | 3 762 398 | 5 338 947 | 26.3% | 17 525 |
| 2026-09-26 | 1 877 067 | 3 072 830 | 4 555 523 | 5 926 231 | 7 324 997 | 3 737 369 | 5 338 947 | 26.0% | 17 409 |
| 2026-09-25 | 1 879 014 | 3 086 952 | 4 590 163 | 5 959 159 | 7 368 420 | 3 758 136 | 5 368 612 | 26.1% | 17 475 |
| 2026-09-24 | 1 873 021 | 3 059 427 | 4 549 236 | 5 906 025 | 7 302 720 | 3 724 627 | 5 320 743 | 26.1% | 17 583 |
| 2026-09-23 | 1 868 163 | 3 022 893 | 4 496 215 | 5 835 498 | 7 215 514 | 3 680 149 | 5 257 205 | 26.2% | 17 655 |
| 2026-09-22 | 1 877 401 | 3 027 885 | 4 511 601 | 5 834 987 | 7 214 883 | 3 700 748 | 5 256 745 | 26.4% | 17 769 |
| 2026-09-21 | 1 882 113 | 3 046 263 | 4 542 905 | 5 880 612 | 7 271 297 | 3 729 575 | 5 297 848 | 26.9% | 18 053 |
| 2026-09-20 | 1 882 113 | 3 054 454 | 4 569 394 | 5 880 612 | 7 271 297 | 3 734 983 | 5 297 848 | 26.1% | 17 563 |
| 2026-09-19 | 1 883 771 | 3 055 264 | 4 569 394 | 5 880 612 | 7 271 297 | 3 734 983 | 5 297 848 | 25.9% | 17 386 |
| 2026-09-18 | 1 890 472 | 3 048 445 | 4 544 758 | 5 848 906 | 7 230 955 | 3 714 846 | 5 269 285 | 26.0% | 17 459 |
| 2026-09-17 | 1 882 992 | 3 035 899 | 4 534 017 | 5 844 089 | 7 226 137 | 3 719 311 | 5 264 945 | 26.1% | 17 421 |
| 2026-09-16 | 1 900 127 | 3 049 426 | 4 559 911 | 5 868 407 | 7 256 206 | 3 721 945 | 5 286 853 | 26.2% | 17 616 |
| 2026-09-15 | 1 900 270 | 3 036 246 | 4 546 462 | 5 851 099 | 7 234 804 | 3 710 967 | 5 271 260 | 26.3% | 17 750 |
| 2026-09-14 | 1 886 387 | 3 018 220 | 4 502 440 | 5 816 361 | 7 189 180 | 3 668 080 | 5 239 965 | 26.8% | 18 067 |
| 2026-09-13 | 1 886 387 | 3 012 980 | 4 493 270 | 5 816 361 | 7 165 652 | 3 668 080 | 5 239 965 | 26.3% | 17 733 |
| 2026-09-12 | 1 877 677 | 3 006 430 | 4 479 698 | 5 816 361 | 7 178 752 | 3 688 935 | 5 239 965 | 25.9% | 17 543 |
| 2026-09-11 | 1 869 621 | 2 983 062 | 4 448 425 | 5 789 102 | 7 130 564 | 3 663 409 | 5 233 442 | 26.1% | 17 785 |
| 2026-09-10 | 1 867 353 | 2 967 323 | 4 424 956 | 5 756 281 | 7 092 943 | 3 644 081 | 5 205 830 | 26.2% | 17 860 |
🔧 Exactly how we calculate
Every step from the raw ad to the figures above. If you would compute it differently, the raw snapshot is downloadable — redo the maths.
The formula
érték = (salary_min + salary_max) / 2 ← sáv-közép × periódus_szorzó ← yearly ÷12 · monthly ×1 · daily ×21 · hourly ×160 × árfolyam[currency] ← EKB középárfolyam, HUF-ra medián = percentile_cont(0.5) WITHIN GROUP (ORDER BY érték) transzp = n / total_n ← bért kiíró / összes aktív hirdetés
One ad yields one value. We take the range midpoint, convert the period to monthly, then to forint — in that order.
What the sample consists of
Currency
USD 14 896
EUR 2 134
GBP 699
PLN 438
CAD 281
HUF 54
INR 47
CHF 33
Stated period
yearly 16 496
monthly 1 568
hourly 651
daily 46
Range type
18 761 two-sided range (min–max) ·
0 floor only (“from”)
Freshness
We re-check ads at their source daily. Verified live within the last 2 days:
18 073 / 18 761
(96.3%)
Exchange rates
Today (ECB reference) · 2026-10-09
EUR 365.1 USD 325.8 GBP 430.7 PLN 83.3
Fixed base · 2026-07-26
EUR 361.9 USD 318.1 GBP 423.8 PLN 83.9
Update schedule
Daily snapshot at 06:55 (after ad imports and location normalisation).
Raw data
The full daily snapshot — every breakdown and segment, including the rates used:
⬇ /salaries/data.jsonFree to use with attribution (CC BY 4.0).
What we exclude, and why
- ✕ Ads without pay — we do not estimate. They only appear in the transparency denominator.
- ✕ Pay without a period — we never guess yearly vs monthly. The ad then stays without pay.
- ✕ Plausibility filter: ranges that cannot be interpreted are skipped at import rather than transformed.
- ✕ Segments below 15 ads are not shown — both for noise and identifiability.
- ✕ Outliers are NOT trimmed or smoothed. Whatever passes the filter stays — p10–p90 shows the spread.
Definitions
- ›Median: PostgreSQL
percentile_cont(0.5)with linear interpolation — the true interpolated value, not the nearest item. - ›Range midpoint:
(min + max) / 2. Where only a floor exists, it is used for both ends. - ›median_fix: the same, but at the rate fixed on the base day — only this is valid for time-series comparison.
- ›Transparency rate:
n / total_n, where the denominator is all active ads in the segment, with and without pay.
⚠️ What this figure does NOT tell you
- •It measures advertised, not paid, salary. The two can differ in both directions.
- •It excludes bonus, equity, benefits and 13th month — ads rarely quantify these.
- •Not representative of the whole labour market: it measures what is advertised through our sources.
- •Figures are gross, and tax systems differ by country — net comparison needs a separate calculator.
🔬 How we measure
- • The headline figure is the MIDPOINT of the range — neither floor nor ceiling. Both ends are reported separately.
- • Since 99.8% of the data is quoted in foreign currency, every movement is reported twice: at a fixed rate (real market movement) and at the daily rate (forint value). The difference is the currency effect.
- • We only count what the employer published in the ad. We do not ask visitors for their salary, and we do not estimate.
- • Ranges in different currencies and periods (year/month/day/hour) are converted to gross HUF/month at the daily reference rate. We never guess the period: if the source does not state it, the ad stays without salary.
- • A segment appears only with at least 15 ads behind it. Regions are reported separately, because a single blended average would hide the differences.
- • Movement is computed from our own daily snapshots, not from ad posting dates — so the timing of our imports cannot distort the trend.
- • p10–p90 marks the bottom and top tenth of the field, p25–p75 the middle half. Outliers are neither trimmed nor smoothed — the distribution is shown as it is.
An indicative market picture of advertised salary ranges; not advice, and not a survey of actually paid salaries.
Detailed salary statistics →