Let us first reduce this problem from an infinite combinatorics problem to a finite combinatorics problem.
Suppose that $g_{0},\dots,g_{n-1}:\omega\rightarrow\alpha$ are functions such that
$g_{i}^{-1}[\{j\}]$ is infinite for each $m<\alpha$. Then let $\simeq$ be the congruence on $\omega$ where we set $x\simeq y$ iff $g_{i}(x)=g_{i}(y)$ for each $i$. Then let $X=\omega/\simeq$, and let $f_{i}:X\rightarrow\alpha$ be the surjective function where $f_{i}([x])=f_{i}(x)$. Then $X$ is a finite set with $|X|\leq\alpha^{n}$, each mapping $g_{i}:X\rightarrow\alpha$ is surjective, and whenever $x,y\in X$, there is some $i$ where $f_{i}(x)=f_{i}(y)$.
Fact: For $\alpha<\omega$, $B_{\alpha}$ is the least natural number $n$ such that there exists a finite set $X$ and surjective functions $f_{0},\dots,f_{n-1}:X\rightarrow\alpha$ such that if $x,y\in X$, then $f_{i}(x)=f_{i}(y)$ for some $i$.
We can use the probabilistic method to get upper bounds for $B_{\alpha}$ for all finite $\alpha$. I have made no attempt to optimize these upper bounds since I just wanted to use the probabilistic method and I want to see how much the other answerers can beat my probabilistic method technique.
Functions selected at random
Let $r$ be a natural number. Suppose that $X$ is a finite set and $\alpha$ is a finite ordinal. Let
$f_{0},\dots,f_{n-1}:X\rightarrow\alpha$ be functions selected independently uniformly at random. Let $x,y\in X,x\neq y$ be selected at random.
Then for random $i$, we have $P(f_{i}(x)\neq f_{i}(y))=\frac{\alpha-1}{\alpha}$. Therefore, by the independence of the functions $f_{i}$, we know that
$P(\forall i,f_{i}(x)\neq f_{i}(y))=(\frac{\alpha-1}{\alpha})^{n}$. Therefore,
$$P(\exists x,y((x\neq y)\wedge\forall i,f_{i}(x)\neq f_{i}(y)))\leq\frac{|X|(|X|-1)}{2}\cdot(\frac{\alpha-1}{\alpha})^{n}$$.
Now, the number of functions from $X$ to $\alpha$ is $\alpha^{r}$ while the number of surjections from $X$ to $\alpha$ is
$$\sum_{k=1}^{\alpha}(-1)^{\alpha-k}\binom{\alpha}{k}k^{r}$$.
Therefore, the probability that a randomly selected function from $X$ to $\alpha$ is surjective is
$$\sum_{k=1}^{\alpha}(-1)^{\alpha-k}\binom{\alpha}{k}\big{(}\frac{k}{\alpha}\big{)}^{|X|}$$.
That is a complicated formula, so let's just work with an approximation.
The set of all functions $f:X\rightarrow\alpha$ with $i\not\in f[X]$ has cardinality
$(\alpha-1)^{r}$. Therefore, the probability that $i\not\in f[X]$ is $(\frac{\alpha-1}{\alpha})^{r}$. Therefore, the probability that $f$ is not surjective is at most $\alpha\cdot(\frac{\alpha-1}{\alpha})^{r}$. Therefore, the probability that some $f_{i}$ is non-surjective is at most
$$n\alpha\cdot(\frac{\alpha-1}{\alpha})^{r}.$$
We conclude that the probability that either some $f_{i}$ is non-surjective or there exists some $x,y$ where for all $i$, we have $f_{i}(x)=f_{i}(y)$ is at most
$$n\alpha\cdot(\frac{\alpha-1}{\alpha})^{r}+\frac{r(r-1)}{2}\cdot(\frac{\alpha-1}{\alpha})^{n}.$$
Therefore, if we select $n$ and $|X|$ such that
$$n\alpha\cdot(\frac{\alpha-1}{\alpha})^{r}+\frac{r(r-1)}{2}\cdot(\frac{\alpha-1}{\alpha})^{n}<1,$$
then we know that there are $f_{0},\dots,f_{n-1}$ where each $f_{i}$ is surjective and where for all $x,y$, there is some $i$ with $f_{i}(x)=f_{i}(y)$.
A modified distribution where functions are surjective
Let us now change the distribution of the functions $f_{0},\dots,f_{n-1}$ in order to guarantee that these functions are surjective.
Suppose that $X$ is a set where $|X|=r$. Let $A_{0},\dots,A_{n-1}$ be randomly selected subsets of $X$ of cardinality $\alpha$. Let
$g_{i}:A_{i}\rightarrow\alpha$ be a random bijection for $0\leq i<n$, and let $h_{i}:X\setminus A_{i}\rightarrow\alpha$ for all $i$. Let
$f_{i}:X\rightarrow\alpha$ be the function where $f_{i}=g_{i}\cup h_{i}$ for all $i$. We have now guaranteed that each function $f_{i}$ is surjective.
Let us now run the same calculation as before.
Suppose $x,y\in X$ are randomly selected with $x\neq y$. Suppose now that $0\leq i<n$ is selected at random. Then $P(x,y\in A_{i})=(\frac{\alpha}{|X|})^{2}$ and in this case $f_{i}(x)\neq f_{i}(y)$. Now, $$P(f_{i}(x)=f_{i}(y)|x\not\in A_{i}\text{ or }y\not\in A_{i})=\frac{1}{\alpha}.$$
Therefore, $$P(f_{i}(x)=f_{i}(y))=[1-(\frac{\alpha}{r})^{2}\cdot\frac{1}{\alpha}$$, and
$$P(f_{i}(x)\neq f_{i}(y))=1+\frac{\alpha}{r^{2}}-\frac{1}{\alpha}.$$
Therefore, for randomly selected $x,y,x\neq y$,
$$P(\forall i,f_{i}(x)\neq f_{i}(y))=(1+\frac{\alpha}{r^{2}}-\frac{1}{\alpha})^{n}.$$
Therefore,
$$P(\exists x,y(x\neq y)\wedge\forall i,f_{i}(x)\neq f_{i}(y))
\leq\frac{r\cdot(r-1)}{2}(1+\frac{\alpha}{r^{2}}-\frac{1}{\alpha})^{n}.$$
Thus, if $r,n$ are selected such that
$$\frac{r\cdot(r-1)}{2}(1+\frac{\alpha}{r^{2}}-\frac{1}{\alpha})^{n}<1$$, then we know that we can select surjective $f_{0},\dots,f_{n-1}$ such that if $x\neq y$, then there is some $i$ with $f_{i}(x)=f_{i}(y)$. We may now solve this inequality to obtain:
$$n>\frac{\ln(2)-\ln(r)-\ln(r+1)}{\ln(r^{2}\alpha+\alpha-r^{2})-\log(r^{2}\alpha)}$$.
Therefore, if $\alpha,r,n$ are integers with $r>\alpha$ and $$n>\frac{\ln(r)+\ln(r+1)-\ln(2)}{\log(r^{2}\alpha)-\ln(r^{2}\alpha+\alpha-r^{2})},$$ then $B_{\alpha}<n$.