IMHO, you really have to embrace dispatch-oriented programming, and that includes being scrupulous about avoiding type instability. You also have to be a bit conscious about allocations, since it's easy to write Julia code (especially if you're trying to write in a "vectorized" style as is common in R, Python, Matlab) that generates absurd numbers of allocations, which must then be garbage-collected. But also easy to avoid those allocations if you know.
It took about two years, but after picking up more of this, I was eventually able to switch everything my group does from a two-language solution of matlab for scripts and plotting and C (with MPI) for HPC to all-Julia. This [1] was originally targeted at academics making the same switch, but much of it could be relevant to those with an R background as well.
[1] https://github.com/brenhinkeller/JuliaAdviceForMatlabProgram...