ING Wholesale Banking serves large corporates and financial institutions with lending, capital markets, payments and trade services. Its stack pairs Java/.NET on OpenShift and Kubernetes with LoanIQ, Swift and Chainalysis, alongside a heavy testing toolchain (Selenium, Playwright, JMeter, Azure Test Plans), which points to engineering focused on regulated, high-assurance transaction processing. Hiring is accelerating and finance-led, with active projects around straight-through processing and zero-touch deal capture.
Notable leadership hires: Director CFA, Head of HR, Chief Financial Officer, Lead Engineer
ING Wholesale Banking is the corporate and institutional banking arm of ING, headquartered in Amsterdam with 10,001+ employees. It serves large corporations, multinationals and financial institutions across more than 40 countries. Its offering spans specialised lending, corporate finance, debt and equity markets, payments and cash management, and trade and treasury services. Sustainable finance and advisory are a stated focus area. Current hiring spans Europe and Asia, including the Netherlands, Poland, Romania, Hungary, Singapore, Japan, South Korea and the Philippines.
Java, .NET and Python on OpenShift, Kubernetes, Docker, Helm and Istio, with Azure DevOps, SonarQube, Fortify and Artifactory, plus banking tools like LoanIQ, Swift and Chainalysis.
Hiring spans the Netherlands, United Kingdom, Luxembourg, Italy, Poland, Hungary, Romania, Turkey, Singapore, Japan, South Korea and the Philippines.
Job posts point to straight-through data processing, zero-touch deal capture, corporate e-banking implementation, platform migrations and transformation of transaction services.
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ING Wholesale Banking'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.