Network engineering is full of vendor buzzwords and supposed new paradigms. It’s a daunting domain to hire for. Albeit more formalised than software development, nothing in data networking is really new⁽¹⁾. So for hiring and talent acquisition teams, a candidate’s soft and hard skills are mostly alike for each of the network specialisations below.
Roughly speaking there are
5 network engineering specialisations and each share many common technologies and fundamental competencies.
- Optical / Transmission
- Telecommunication(Telco) / Mobile
- Backbone / Internet Service Provider(ISP)
- Data Center / Storage
Note: We are not explicitly calling out ‘Network Security’ or ‘Firewall Engineer’ as both security and technical risk management are qualities of all the domains above.
Experience and Evolution
Even after categorising the main network engineering specialisations, there still exists
3 traditional functions in each area; that of operations, implementation, and design/architecture. There may be separate teams for each of these functions but increasingly there is partial or full overlap.
Today there are even greater mixed skills roles such as SRE (Site Reliability Engineer) a term coined by Google, NRE (Network Reliability Engineer) coined by Amazon, and the all encompassing NetDevOps. Each seek to diminish silos, reduce manual intervention, and/or increase the use of automation to improve quality.
These new multiskilled roles have arisen due to the criticality of modern networks coupled with inefficiencies in traditional organisational structures.
More Structured Hiring
‘Structured Hiring’ helps bring about a more consistent, evidence based, and auditable process in each step of an organisation’s hiring endeavours.
The intent of structured hiring is to:
- Increase the quality of hires
- Increase Employee Lifetime Value (ELV)
- Reduce costs (by eliminating duplication of effort and facilitating faster decision making)
- Reduce ‘Time to Hire’ (with better collaboration and reduced human engagement)
- Reduce the impact of unconscious bias (with consistent systematic processes)
- Decrease the likelihood of bad hires (via an evidence based approach coupled with increased screening and transparency)
Also, by requiring the demonstration of skills and not solely relying upon biased CVs, equivocal endorsements, or self-populated profiles, the bar can be raised successively and scientifically throughout the hiring process.
Structured Hiring is a topic as broad as it is deep and it constantly evolves. We shall focus on
2 specific aspects in relation to hiring network engineers.
- Where do we normally find network engineers? (Sourcing Talent)
- How do we know they can do what they claim? (Screening Talent)
Whether posting job advertisements on traditional platforms, trawling through internal databases, or leveraging professional networks seeking candidates, the holy grail would be that of a perfect candidate arriving pre-screened for both attitude and experience (with the added assumption being they are looking for new opportunities and are ready to move to a new role!). In such a perfect world, all that would remain would be doing due diligence, negotiating an offer, and ensuring culture add for the organisation.
Unfortunately the above is unrealistic, yet more and more services are beginning to provide expert pre-screened talent pools whereby they themselves (or their expert platforms) proxy the sourcing and screening on an organisations behalf. This then helps to populate an organisation’s funnel faster… with candidates who are actually in possession of the skills claimed.
Traditional hiring decisions may seem a bit haphazard when compared to more modern data-driven determinations. Previously, a recruiter, hiring manager, or talent acquisition team member (with or without domain expertise) may have been manually sifting through applicant’s CVs, scanning databases for keywords using ‘Boolean’ searches, or using other traditional methods. This is the top of the ‘funnel’ in most scenarios. Unfortunately though, some of the best candidates can be easily overlooked. Conversely and undesirably, those who look good on ‘paper’ (or who game the system with simple keyword manipulation) may make it to the next phase.
So, if initial screening isn’t optimising for the widest and most accurate funnel, then human time spent phone screening, videoconferencing, and in person interviewing might not be targeting the best candidates but rather the best marketers.
Optimally, one wants to hire for both attitude and experience with as much verification of skills performed as economically possible. From a scalability and automation perspective, it is actually easier and cheaper to test for hard skills as early as possible in the hiring pipeline. This is to highlight those with the required skills and also to weed out those who are not serious or invested in the role and process. This then means that the hiring team has its own utility maximised and their expensive human time is kept to an optimal minimum. Some organisations set tasks or challenges which try to test for a specific skill or capability yet many require expert human time to correct or review. Also, some organisations set take home projects with unreasonable requests on a candidate’s time e.g.
20 hours or more.
In almost all network engineering specialisations, fundamental hard skills include a working knowledge of (but are not limited to): IPv4, IPv6, TCP/IP, arp, 802.3, SNMP, syslog, NTP, SSH, BGP, OSPF, VRF, MPLS, VTP, 802.3af, VLANs, subnetting, 802.1q, 802.3ad, STP, LLDP, multicast, VRRP, GLBP, DHCP, ACLs, NAT, IPFIX.
2hours for an automated initial technical screen. By using ML (Machine Learning) and NLP (Natural Language Processing) we extract testable skills and then build custom simulations to test claimed skills. We call the process of testing candidates in real live scenarios Simulation Based Screening. It allows for wider funnels and less bias whilst saving costs and reducing time-to-hire.
Back to Basics
Indeed the challenge is to verify that a network engineering candidate in a hiring funnel actually has, and can also demonstrate, the fundamental and/or desirable skills required for a role. By validating the correctness and accuracy of a position description and by verifying the candidate’s skills, faster decisions can be made that also lead to better quality hires. As we’re increasingly able to simulate different environments, the future may yet hold a version of Star Trek’s Kobayashi Maru test, but until then we have Simulation Based Screening. If you don’t have enough evidence to back up your decisions (i.e. are unable to objectively contrast and compare candidates), then it’s likely unconscious biases will lead to expensive bad hires in the near future.