Comparación de salarios por nivel de experiencia en Perú
| # | Nivel de experienciaNivel | Profesión AProf. A | DiferenciaDif. | Profesión BProf. B | Profesión AProf. A | DiferenciaDif. | Profesión BProf. B |
|---|---|---|---|---|---|---|---|
| 1 | Junior | S/4,000PEN | S/2,000PEN | S/6,000PEN | ₿0.0161 | ₿0.0081 | ₿0.0242 |
| 2 | Semi-Senior | S/6,000PEN | S/2,500PEN | S/8,500PEN | ₿0.0242 | ₿0.0094 | ₿0.0336 |
| 3 | Senior | S/8,500PEN | S/3,000PEN | S/11,500PEN | ₿0.0336 | ₿0.0108 | ₿0.0444 |
| 4 | Supervisor | S/11,000PEN | S/3,000PEN | S/14,000PEN | ₿0.0430 | ₿0.0108 | ₿0.0538 |
| 5 | Gerente | S/14,000PEN | S/2,500PEN | S/16,500PEN | ₿0.0551 | ₿0.0094 | ₿0.0645 |
- ProfesiónA Analista de Datos ProfesiónA Analista de Datos
- ProfesiónB Administrador de Data Warehouse ProfesiónB Administrador de Data Warehouse
Comparación de salarios promedio por ciudad en Perú
| # | Ciudad | Profesión AProf. A | DiferenciaDif. | Profesión BProf. B | Profesión AProf. A | DiferenciaDif. | Profesión BProf. B | |
|---|---|---|---|---|---|---|---|---|
| 1 | S/7,000PEN | S/3,500PEN | S/10,500PEN | ₿0.0268 | ₿0.0132 | ₿0.0400 | ||
| 2 | S/6,500PEN | S/3,500PEN | S/10,000PEN | ₿0.0260 | ₿0.0128 | ₿0.0388 | ||
| 3 | S/6,500PEN | S/3,500PEN | S/10,000PEN | ₿0.0260 | ₿0.0128 | ₿0.0388 | ||
| 4 | S/6,500PEN | S/3,500PEN | S/10,000PEN | ₿0.0260 | ₿0.0128 | ₿0.0388 | ||
| 5 | S/6,500PEN | S/3,500PEN | S/10,000PEN | ₿0.0260 | ₿0.0128 | ₿0.0388 | ||
| 6 | S/6,500PEN | S/3,500PEN | S/10,000PEN | ₿0.0260 | ₿0.0128 | ₿0.0388 | ||
| 7 | S/6,500PEN | S/3,500PEN | S/10,000PEN | ₿0.0260 | ₿0.0128 | ₿0.0388 | ||
| 8 | S/6,000PEN | S/3,000PEN | S/9,000PEN | ₿0.0241 | ₿0.0119 | ₿0.0360 | ||
| 9 | S/6,000PEN | S/3,000PEN | S/9,000PEN | ₿0.0241 | ₿0.0119 | ₿0.0360 | ||
| 10 | S/6,000PEN | S/3,000PEN | S/9,000PEN | ₿0.0241 | ₿0.0119 | ₿0.0360 | ||
| 11 | S/6,000PEN | S/3,000PEN | S/9,000PEN | ₿0.0241 | ₿0.0119 | ₿0.0360 | ||
| 12 | S/6,000PEN | S/3,000PEN | S/9,000PEN | ₿0.0241 | ₿0.0119 | ₿0.0360 | ||
| 13 | S/6,000PEN | S/3,000PEN | S/9,000PEN | ₿0.0241 | ₿0.0119 | ₿0.0360 | ||
| 14 | S/6,000PEN | S/3,000PEN | S/9,000PEN | ₿0.0241 | ₿0.0119 | ₿0.0360 | ||
| 15 | S/6,000PEN | S/3,000PEN | S/9,000PEN | ₿0.0241 | ₿0.0119 | ₿0.0360 | ||
| 16 | S/6,000PEN | S/3,000PEN | S/9,000PEN | ₿0.0241 | ₿0.0119 | ₿0.0360 | ||
| 17 | S/6,000PEN | S/3,000PEN | S/9,000PEN | ₿0.0241 | ₿0.0119 | ₿0.0360 | ||
| 18 | S/6,000PEN | S/3,000PEN | S/9,000PEN | ₿0.0241 | ₿0.0119 | ₿0.0360 | ||
| 19 | S/6,000PEN | S/3,000PEN | S/9,000PEN | ₿0.0241 | ₿0.0119 | ₿0.0360 | ||
| 20 | S/6,000PEN | S/3,000PEN | S/9,000PEN | ₿0.0241 | ₿0.0119 | ₿0.0360 | ||
| 21 | S/6,000PEN | S/3,000PEN | S/9,000PEN | ₿0.0241 | ₿0.0119 | ₿0.0360 | ||
| 22 | S/6,000PEN | S/3,000PEN | S/9,000PEN | ₿0.0241 | ₿0.0119 | ₿0.0360 | ||
| 23 | S/5,500PEN | S/3,000PEN | S/8,500PEN | ₿0.0219 | ₿0.0108 | ₿0.0328 | ||
| 24 | S/5,500PEN | S/3,000PEN | S/8,500PEN | ₿0.0219 | ₿0.0108 | ₿0.0328 | ||
| 25 | S/5,500PEN | S/3,000PEN | S/8,500PEN | ₿0.0219 | ₿0.0108 | ₿0.0328 | ||
| 26 | S/5,500PEN | S/3,000PEN | S/8,500PEN | ₿0.0219 | ₿0.0108 | ₿0.0328 | ||
| 27 | S/5,500PEN | S/3,000PEN | S/8,500PEN | ₿0.0219 | ₿0.0108 | ₿0.0328 | ||
| 28 | S/5,500PEN | S/3,000PEN | S/8,500PEN | ₿0.0219 | ₿0.0108 | ₿0.0328 | ||
| 29 | S/5,500PEN | S/3,000PEN | S/8,500PEN | ₿0.0219 | ₿0.0108 | ₿0.0328 | ||
| 30 | S/5,500PEN | S/3,000PEN | S/8,500PEN | ₿0.0219 | ₿0.0108 | ₿0.0328 |
- ProfesiónA Analista de Datos ProfesiónA Analista de Datos
- ProfesiónB Administrador de Data Warehouse ProfesiónB Administrador de Data Warehouse
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