Description & Requirements
As a Network Engineer/Designer you’ll be working in a small team, responsible for design and build components within the Service Delivery Platform (SDP) and TelcoCloud (Mobile Network Datacentre Infrastructure). This exciting often innovative and challenging role is perfect for a self-motivated candidate.
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Design and build work within our team on our SDP and TelcoCloud DataCentre networks.
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Working with Internal and Customer Technical teams to design and build, network connectivity for Spark’s Service edge and Mobile networks.
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Working with External partners in building and designing networks to support various network and mobile functions.
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The ideal candidate needs to have at least 5-6 years of network experience, in a senior role (support or design).
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Knowledgeable across the Arista product range.
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Technology proficiency
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Arista and Cisco – Fully proficient in configuration, design and operate.
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Data Centre – Leaf/Spine Architecture, associated Layer 2/3 protocols for Data Centres.
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Routing – BGP, OSPF
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Switching – Layer 2 protocols
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Scripting – Proficiency in PHP, Python or similar etc.
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Firewalling – Checkpoint, FortiGate – Basic proficiency in design and operate.
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VMWare – Proficient in understanding building blocks of VMWare NSX and vDS virtual networking structures.
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- Wellbeing - Comprehensive medical insurance, life and income protection. Access to wellbeing coaches, EAP and in-house Specialist Clinical support through our leading Mahi Tahi Wellness programme.
- Hybrid ways of working - for most teams at Spark this means being in the office for 4 days a week, and 1 day being flexible.
- Leave - in addition to four weeks annual leave, we offer purchased leave, enhanced parental leave support and study leave.
- Spark Credit – we provide permanent employees with $120 monthly Spark credit to use on any of our amazing products.
- Spark Share scheme – periodically we offer the opportunity to buy into our share scheme.
- Career development – access to an internal marketplace that connects employees with experiential, on the job learning across Spark.