Where can you find the most Bilingual WAN Engineers?

I was reading a discussion in the Boolean Strings group on LinkedIn and someone was having difficulty in locating a bilingual (Spanish) WAN Engineer in the Denver, CO area. It sounded like as good of a challenge as any, so I decided to take a crack at seeing what I could find by searching the Internet via Google, LinkedIn, Monster, and an internal database.

 

As a first swing, I crafted this search that can be run on any resume database recognizing basic Boolean (internal database/ATS, Monster, Careerbuilder, etc):

 

(WAN or “Wide Area” or ATM or Frame) and cisco and router* and (senior or lead or architect or engineer) and network* and Spanish and (fluently or fluency or fluent or native or bilingual or bi/lingual or “bi lingual” or language* or conversational)

 

Monster yielded 26 results in a 30 mile radius from Denver.

 

My internal resume database turned up 166 results in Denver specifically. It pays to have a Talent Warehouse. :-)

 

As for the search I chose to begin with – while not everyone will mention descriptive words such as “native,” “fluent,” or “bilingual,”  it is a good idea to start there because it nearly guarantees fluency.  

After you exhaust those fluency-related words,  NOT them out to find people who simply mention “Spanish” and sort through them. For example:

 

(WAN or “Wide Area” or ATM or Frame) and cisco and router* and (senior or lead or architect or engineer) and network* and Spanish and not (fluently or fluency or fluent or native or bilingual or bi/lingual or “bi lingual” or language* or conversational)

 

Using the site: command via Google to search LinkedIn, I went with this search:

 

site:linkedin.com (WAN | “Wide Area” | ATM | Frame) cisco ~router  (senior | lead | architect | engineer) ~network Spanish “greater denver area” -intitle:directory -inurl:updates -inurl:updates

 

That yielded 0 results. Once i took out the Spanish, I got 42 tight results.  So the limiting factor is the word “Spanish.” 

 

Sourcing LinkedIn can be a challenge because LinkedIn is not a resume database.  Most people do not fill out their profiles completely when it comes to their employment history, and even those that do don’t often provide much detail or information.  I am not surprised at all that there are not many people who mention that they are bilingual on their LinkedIn profile.  LinkedIn is a great source of talent, but it is typically a low yield source of highly specific talent.

 

I then moved on to running a search on Google to see what I could find on the Internet: 

 

(intitle:resume | inurl:resume) (WAN | “Wide Area” | ATM | Frame) cisco ~router  (senior | lead | architect | engineer) ~network Spanish 80001..80640 -~job -~jobs

 

That search yielded 2 results, 1 of which is in Denver, and he’s a TS cleared CCIE. Sweet.

 

Switching it up from a zip code range to area codes, I ran this:

 

(intitle:resume | inurl:resume) (WAN | “Wide Area” | ATM | Frame) cisco ~router  (senior | lead | architect | engineer) ~network Spanish (720 | 303) -~job -~jobs

 

That search only yielded 1 result, which was non-local.

 

This exercise clearly illustrates the point I try to make over and over – for highly specific hiring profiles (and I don’t limit this to rare skills – just highly specific) – the Internet is not really the cornucopia of resumes (yes, that was a purposefully placed Thanksgiving reference) many people make it out to be, or falsely assume it to be.  LinkedIn also isn’t the panacea of talent for highly specific hiring profiles. The major job boards of course will represent relatively well because they are by design repositories of resumes, and very large ones at that. So even rare/highly specific skills and experience are represented in solid quantities. 

 

And last, but most certainly not least, a well stocked internal resume database, ATS, or Talent Warehouse can actually be a sourcer’s or recruiter’s most effective weapon in the War for Talent. In this exercise, the internal resume database (166 results) trumped Monster (26), LinkedIn (0), and the mighty Internet (2).

 

Google, Internet Sourcing, Job Boards, LinkedIn, Resume Sourcing

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