Ingeniero de Datos

About the role

The Data Engineer will design and implement analytical enablements—including data models, pipelines and data products—using DataOps, MLOps and information governance practices. The role supports AI cells and automation teams, ensuring data quality, traceability and availability for decision‑making within the bank.

Key responsibilities

• Design and build data capabilities that feed analytical and AI initiatives, guaranteeing integration, transformation and availability of information.
• Provide specialized technical support to AI and automation squads on corporate platforms, ETL/ELT processes, solution deployment and scalable, secure data productization.
• Create and maintain transversal data models that embed business expertise across domains for multiple use cases.
• Implement analytical enablements following the Group’s information‑governance standards to ensure efficiency, quality and standardization.
• Operate data and analytics solutions under DataOps and MLOps practices, maintaining reliability and traceability in production environments.
• Develop and operationalize analytical variables, KPIs and inference models related to customers, products, channels and services.
• Promote best practices for publishing, integrating and automating analytical assets within the bank’s data and AI ecosystem.
• Coach analytical talent on the corporate data platform, encouraging sound development practices.

Required profile

• Solid experience in data engineering and building data pipelines.
• Strong background in data modeling and information architecture.
• Knowledge of DataOps, MLOps and information‑governance frameworks.
• Advanced programming and analytical abilities.
• Consultative mindset to enable and collaborate with analytical teams.

Required skills

• Data pipelines
• Data modeling
• Data architecture
• DataOps
• MLOps
• Information governance
• ETL
• ELT