Data Taxonomy Architect & AI Solutions Lead

Accenture México; Ciudad de México; Presencial; MXN 900.000 - 1.500.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Career development

Innovative tools and methodologies

Direct contact with experts worldwide

International projects

Teamwork and collaboration

Descripción de la vacante

Accenture México seeks a data-focused professional to join our team in Mexico City. You will tackle data taxonomy, architecture, and Generative AI initiatives across multiple projects, collaborating with experts worldwide to deliver innovative solutions.

The role involves defining data migration strategies, building scalable data product architectures, and ensuring data quality through lifecycle management. A technical diploma is required, with strong emphasis on AI-driven data processes.

Formación

• Master proficiency in Data Taxonomy and Data Architecture.
• 4+ years of experience in data-related roles.
• Diploma in a relevant field is required.

Responsabilidades

• Define and implement data migration and modernization architecture.
• Develop and maintain data product architecture aligning with goals.
• Implement data lifecycle management to optimize quality and usability.
• Leverage Generative AI models to enhance product and system quality.
• Analyze Generative AI performance and provide design recommendations.
• Design end-to-end Generative AI products tailored to business requirements.
• Provide implementation guidance during delivery of Generative AI solutions.

Conocimientos

Data Taxonomy

Data Architecture

Generative AI

Data Modeling

Educación

Technical Diploma

Descripción del empleo

Accenture México seeks a data-focused professional to join our team in Mexico City. You will tackle data taxonomy, architecture, and Generative AI initiatives across multiple projects, collaborating with experts worldwide to deliver innovative solutions.

The role involves defining data migration strategies, building scalable data product architectures, and ensuring data quality through lifecycle management. A technical diploma is required, with strong emphasis on AI-driven data processes.