Viva.com operates a financial platform for European businesses, with a tech stack spanning Python, Java, TypeScript, and multi-cloud infrastructure (Azure, AWS, GCP). The hiring profile is heavily sales-focused—29 of 49 active roles are in sales—while engineering and data teams remain lean, suggesting a go-to-market and merchant-activation strategy rather than a product-engineering-first operation. Current projects center on merchant onboarding, fraud detection refinement, and regulatory compliance, with stated pain points around detection-rule tuning and control-gap identification.
Viva.com is a fintech bank headquartered in Greece, serving SMEs and businesses across Europe with payment acceptance, card issuing, loans, and deposit accounts. Founded in 2010, the company operates a 1,001–5,000-person organization and maintains an ecosystem of over 450 technology partners. The platform connects to local payment schemes and alternative payment methods across the continent. Viva.com is based in Marousi, Attica, and is actively hiring across nine European countries (Greece, Germany, Italy, Croatia, United Kingdom, Ireland, Spain, Slovenia, Hungary, Portugal), with particular emphasis on sales, operations, and security roles.
Python, Java, TypeScript for development; Azure, AWS, GCP for cloud infrastructure; Apache Airflow, Kubernetes, and Azure Kubernetes Service for orchestration; SQL Server, MySQL, MongoDB for databases; Power BI and Tableau for analytics.
Merchant onboarding and activation, fraud-detection refinement, regulatory risk assessment, control-systems development, new product launches, revenue model refinement, and integration of innovative payment technologies across omnichannel channels.
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.