We know that Eulers number $e$ can be expanded as $$e = 1 + 1 + \frac{1}{2!} + \frac{1}{3!} + \frac{1}{4!} ...$$
An extended definition for the powers of $e$ are: Equation 2
$$e^\lambda = \sum_{k=0}^{\infty}{\frac{\lambda^k}{k!}} $$
Which is something I learned recently in statistics, as it is used in the Poisson pmf.
I was hoping to find a nice story for how this ties into my understanding of Poisson distribution or Euler's number or what trickery was used to prove this infinite series as the common method for calculating the value of an infinite series by substitution fails here. Does anyone have a reference/proof of this infinite series expansion of the powers of $e$?
Edit: as suggested let me add context to narrow down the question and move it more towards stats than math oriented
The pmf of a distribution must sum to 1. The Poisson pmf is defined as the RHS of equation 2 above. To normalise it, it must be divided by a normalisation factor, which happens to be $\frac{1}{e^\lambda}$ I am trying to understand how the RHS which is well understood as the Poisson events, happened to sum to the LHS, and if there is causation there or just coincidence. Because if it is coincidence and we normalise every PMF value by a constant that is slightly off, it would screw up the entire pmf. And Poisson is used to work with small probability values and computationally the probability checks out, but there is nothing better than proof by numerical computation to some decimals?