Automation & AI Operations Analyst

Nadara Services (Spain) S.L.U.; Madrid; Presencial; EUR 30.000 - 40.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Flexible ways of working

Continuous learning and development

Wellbeing initiatives

Descripción de la vacante

Nadara is seeking a Scalable Operations Analyst in Madrid to join the growing Ops team. You will own mid-level tasks across multiple workstreams, maintain dashboards, and drive data-driven improvements using Excel, Power BI, and AI-assisted automation.

You will collaborate with IT, Digital, and NAIT, standardize processes, monitor KPIs, and help design TOM design initiatives while reducing cost-to-serve through automation and data quality improvements.

Formación

• Mandatory: Bachelor's degree or equivalent in any field.
• Preferred: experience in operational/analytical or project coordination role in energy or industrial sector.
• Preferred: demonstrable portfolio of automations, agents, or internal tools built in professional or personal capacity.

Responsabilidades

• Own mid-level operational tasks across all Scalable Operations workstreams.
• Maintain the centralised initiative dashboard and all tracking tools; ensure accuracy and up-to-date status.
• Develop and maintain automations and AI agents to reduce manual effort across Scalable Operations processes.
• Coordinate multi-department inputs, chase stakeholders, and consolidate information to keep momentum on deliverables.

Conocimientos

Advanced Excel

Power BI

Python

SQL

Automation

Educación

Bachelor's degree

Herramientas

Maximo

Dynamics 365

SharePoint

Descripción del empleo

Nadara is seeking a Scalable Operations Analyst in Madrid to join the growing Ops team. You will own mid-level tasks across multiple workstreams, maintain dashboards, and drive data-driven improvements using Excel, Power BI, and AI-assisted automation.

You will collaborate with IT, Digital, and NAIT, standardize processes, monitor KPIs, and help design TOM design initiatives while reducing cost-to-serve through automation and data quality improvements.