Technology and operations arm building Santander's banking platforms
Santander Digital Services runs technology and operations for the Santander group, spanning a hybrid stack where COBOL, DB2, ABAP and Solaris sit alongside AWS, Azure, GCP and Anthropic. Current hiring tilts heavily toward security, with identity tooling (SailPoint IdentityIQ, CyberArk) and SAST/DAST in focus, while job posts point to generative AI voicebots and agentic systems reshaping contact center operations.
Santander Digital Services is the global technology and operations team for the Santander banking group, and it also covers technology and operations for the bank in Spain. Headquartered in Boadilla del Monte in the Community of Madrid, it employs 5,001–10,000 people across multiple countries. Its work spans cloud, data, cybersecurity, software engineering and AI for banking use cases. The stack combines mainframe and enterprise systems such as COBOL, DB2, Oracle and SAP with modern frameworks like Java, Spring Boot, Angular and Python. Current hiring activity is concentrated in Spain and Mexico.
Its stack includes Java, Spring Boot, Angular, Python, COBOL, DB2, Oracle, SAP/ABAP, Apache Airflow, ServiceNow, Jira, and cloud platforms AWS, Azure and GCP, plus security tools like SailPoint IdentityIQ and CyberArk.
Yes, security is the dominant hiring area, with mid and senior roles tied to identity management, privileged access, application security testing (SAST/DAST) and CERT incident investigations.
Job posts reference generative AI voicebots for contact centers, production-grade agentic AI systems, and fine-tuning small language models for regulated banking use cases.
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Santander Digital Services'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.