We use a new dataset and a novel identification strategy to analyze the effects of residential segregation on the employment of migrants in 8 Italian cities. Our data, which are representative of the population of both legal and illegal migrants, allow us to measure segregation at the very local level (the block) and include measures of house prices, commuting costs and migrants' linguistic ability. We find evidence that migrants who reside in areas with a high concentration of non-Italians are less likely to be employed compared to similar migrants who reside in less segregated areas. In our preferred specification, a 10 percentage points increase in residential segregation reduces the probability of being employed by 7 percentage points or about 8% over the average. Additionally, we also show that this effect emerges only above a critical threshold of 15-20% of migrants over the total local population, below which there is no statistically detectable effect. The negative externality associated with residential segregation arises only for the employment prospects of immigrants, whether legal or illegal. We do not find evidence of either spatial mismatch or skill bias as potential explanations of this effect. Statistical discrimination by native employers is the remaining suspect.