Shop Apotheke - React Recruiting

Shop Apotheke is a very fastly growing company valuated currently (November 2020) at more than 2 Billion EUR. The company became our client via recommendation of our recruiting skills. A manager at the Shop Apotheke, for whom we had done free consulting services for, recommended us to the CPO of Shop Apotheke. We started working together in September 2020 and have recruited one top engineers for Shop Apotheke.


The CPO of Shop Apotheke was intensely looking for a senior React.js Engineer to lead part of the software development in his department of a couple of dozens of experts. He was not very satisfied with the results of another external recruiter and wanted more speed and expertise to quicken and above all make the hiring process successful. An engineer was needed who would come into the team and bring in significant value and tackle main technological issues arising like breaking down a monolith of code or steering React.js development back to React core coding standards and best practises.

The following main requirements had to be fulfilled by the candidate, apart from extensive React.js experience and good leadership skills:

  • Willingness to relocate to Cologne or Berlin, where technology branches of Shop Apotheke are found
  • A valid working visa for Germany
  • Expertise in other related technologies like Javascript and Node.js
  • Fluency in German and/or English

Hiring a React Engineer for Shop Apotheke


After meeting up in person with the CPO in Berlin and agreeing to collaborate, we first of all started manually searching for the fitting candidates in our internal and immediate external network

When we were not successful doing that, we deployed our recruiting automation tool on LinkedIn to search and locate React.js engineers in Cologne. Then we moved on to run similar recruiting campaigns in Berlin followed by other regions like Frankfurt Area, Karlsruhe Area, Hamburg Area, Poland, Amsterdam and Brussels Area. The first round of campaigns was not successful after going through more than 2000 profiles. This round of campaigns used very specific parameters like searching if the keyword “React” was present in the Title or About sections of the profiles of potential candidates.

Interestingly, after we loosened up the specificity of our searches and no longer strictly considered the About and Title sections, our campaigns started yielding fruits and we began getting higher quality candidates suitable for the position.



Remote work with initial meeting in Berlin


Spent on work over the period of 8 weeks


Profiles were searched and 1300 contacted

Countlesscandidates who were contacted showed interest in the position


Interviews conducted

Many interested candidates were not deemed qualified. Due to our expertise as engineers too, we are able to filter this quickly


Candidates suggested to client


Candidates accepted for interviews


Reached the final interview round

Candidate hired.Time to hire: 8 weeks


4 weeks of internal searching and running automation campaigns on LinkedIn brought us no results and we could still not present even one candidate to the client. This could have been because of two main reasons:

  • We could not commit high capacity resources of at least 20 hours per week to the project at the beginning (during the first 4 weeks)
  • Our campaigns at the beginning of the search were too specific

Interestingly once we started searching more broadly without filtering the profiles contacted that much, we started finding more quality engineers. We also allocated more time to the project and the intensity helped to lead to success.


Technology Stack


We had to rethink our previous definition of quality profiles for our automation tool on LinkedIn after this project. Quality profiles before this project, mainly meant those profiles that have the required/predefined keywords in their About and Title sections. Profiles which are somewhat full of the right information. It turned out this does not actually translate to expertise or quality of an engineer. The engineers we finally recruited for this project all did not have exemplary LinkedIn profiles. Their CVs were not the best too, but good enough.

The power of our automation tool was confirmed because 4 of the 5 candidates proposed to Shop Apotheke were found by the automation tool via LinkedIn.

We contacted other recruiters and recruiting agencies to help us when we ran into a wall after 4 weeks, a time at which we could not find a single good candidate to present to Shop Apotheke. Some were unwilling to collaborate due to the shared commission fee and others who did, could not deliver. So we’ll be reevaluating our working relationship with other recruiters after this project.

Referrals that came through this project,especially candidates who referred other candidates, were very average. One of the referrals was good enough on paper to be interviewed by us, but not good enough to be presented to the client – Shop Apotheke. Nevertheless referrals is something we are going to do more, but find more efficient ways to use the process. Example: we started focusing on referrals very late in this project and will have that as a focus from the very beginning for upcoming projects.


About Shop Apotheke

Shop Apotheke Europe N.V. is a market-listed online pharmacy with headquarters in Venlo, Netherlands. The company employs a total of more than 1000 employees at locations in Venlo, Berlin, Cologne, Düsseldorf and Tongern. The range of products they offer in their online store includes over-the-counter and prescription drugs, dietary supplements, beauty and health products.

2 800000

Customers supplied via online shop

1 000000

Candidates accepted for interviews

€2 000000

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