Viva.com runs merchant payment acceptance, business accounts, card issuing and financing on a heavily Azure-centric stack (AKS, Service Fabric, App Service) backed by Go, Python and a full observability layer of Datadog, Prometheus, Grafana and PagerDuty. Hiring is accelerating and strongly sales-led across eight European countries, while engineering work centers on moving workloads onto Azure Kubernetes Service and formalizing SLIs and SLOs.
Notable leadership hires: Lead Generation Executive
Viva.com is a privately held financial services company founded in 2010 and headquartered in Marousi, Attica, Greece. It serves businesses across 31 countries with omnichannel payment acceptance, deposit accounts, card issuing, working capital and booking-based financing, and fiscalisation services. Its payment technology turns Android phones and iPhones into card acceptance devices, with direct connections to international and domestic card schemes and local payment methods. The company employs 1,001–5,000 people and recruits across Greece, Italy, Portugal, France, Slovenia, Spain, Hungary and the United Kingdom.
Viva.com builds on Azure (AKS, Service Fabric, App Service, Azure DevOps) with Python and Go, plus Kubernetes, Terraform, Redis, RabbitMQ, SQL Server, MongoDB, and Datadog, Prometheus and Grafana for monitoring.
Yes. Sales dominates Viva.com's open roles, mostly mid-level, with recruiting across Greece, Italy, Portugal, France, Slovenia, Spain, Hungary and the UK, focused on merchant onboarding and lead generation.
Viva.com is headquartered in Marousi, Attica, Greece, and serves businesses in 31 countries across Europe.
Other companies in the same industry, closest in size
Viva.com's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.
