Senior Data Engineer

VASS • Spanish: C1 • IT Consulting & Digital Transformation • AI Consulting & Integration • Python • SQL • 2 days ago
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Salary
≈ $80k – $202k per year (Estimated)
Location
In office
Seniority
Senior

Confirmed on the employer's own hiring board on Oct 5, 2026. First seen by Alion on Jul 1, 2026. VASS scores B on the Alion truth index.

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VASS

VASS is a Madrid technology consultancy founded in 1999 and specialised in digital transformation. It delivers customer experience platforms, data and artificial intelligence projects for banking, retail and telecommunications clients. The group employs several thousand people across Europe and the Americas and is backed by One Equity Partners.
vasscompany.com • HQ: Madrid, Spain • AI Consulting & Integration • IT Consulting & Digital Transformation • 1001-5000 employees • Est. 1999
Tech stack of VASS

Objetivo del rol Profesional encargado de liderar el diseño técnico, arquitectura e implementación de soluciones de datos empresariales críticas. Será referente técnico en definición de estándares, optimización de costos cloud, gobierno del dato y liderazgo de equipos de desarrollo en ambientes corporativos complejos. Responsabilidades principales Diseñar arquitecturas de datos escalables, distribuidas y orientadas a eventos.

Definir estándares técnicos, buenas prácticas de desarrollo y arquitectura. Implementar estrategias de gobierno de datos, calidad, linaje y observabilidad. Gestionar optimización de costos en nube bajo prácticas FinOps.

Liderar revisiones técnicas y acompañar equipos mediante mentoring. Trabajar transversalmente con equipos de IA, Analítica y Arquitectura. Perfil requerido Formación Profesional en Ingeniería de Sistemas, Computación, Informática o carreras afines.

Experiencia más de 6 años en ingeniería/arquitectura de datos. Experiencia en plataformas Cloud y ecosistemas analíticos empresariales. Más de 2 años liderando proyectos de alta complejidad.

Deseable experiencia en sector financiero con dominio profundo de plataformas analíticas a escala. Habilidades Técnicas Clave: Nivel experto en Python, SQL, Spark y PySpark. Dominio avanzado de arquitectura de datos en AWS (Glue, EMR, Athena, S3) e integración con herramientas de analítica y ML (SageMaker, QuickSight).

Experiencia comprobada en despliegues e infraestructura: Docker, Kubernetes, Terraform, Jenkins, Git y Linux. Valoramos muchísimo si vienes de la escuela del sector financiero y tienes experiencia previa navegando en el ecosistema y la arquitectura de datos ADA

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