Data & Ai Lead

hace 2 semanas


Capital Federal Buenos Aires, Argentina Aeros A tiempo completo

Importante empresa de tecnología se encuentra en la búsqueda de un Lead Data Engineer para sumarse al equipo, siendo el responsable de dirigir la estrategia y la gestión de datos dentro de la organización.

**Qué vas a hacer**:
Actuar como asesor técnico confiable para los clientes y resolver problemas complejos de Big Data.
Contribuir a la implementación de grandes sistemas de datos en Google Cloud.
Conocer los productos de Data & AI de Google Cloud Platform para liderar equipos de arquitectos, ingenieros y analistas de datos.
Supervisar, liderar y guiar a los equipos de implementación en la ejecución de proyectos de Datawarehouse Modernization, BI Modernization, MLOps, GenAI, entre otros.
Liderar, entrenar y orientar a un equipo de ingenieros de datos y desarrolladores de BI en un entorno acelerado.
Contribuir a una cultura de colaboración técnica y desarrollo escalable.
Supervisar la arquitectura, el almacenamiento y la gestión de datos para garantizar la disponibilidad, la escalabilidad y el rendimiento de los proyectos de clientes de LATAM.
Identificar oportunidades para la aplicación de tecnologías emergentes en extracción, orquestamiento y técnicas avanzadas de análisis de datos para mejorar los procesos y la toma de decisiones de nuestros clientes.

**Requisitos**:
Experiência previa de al menos 2 años en roles de liderazgo en el campo de datos, inteligencia artificial y/o análisis de datos (excluyente) Conocimiento profundo de bases de datos (SQL / NoSQL) y experiência con herramientas como DBT, Airflow, Hadoop y/o Spark (excluyente) Experiência práctica en programación orientada a BigData tales como Python, Java y/o R (excluyente) Experiência en proyectos de migración a Google Cloud desde Cloudera, Teradata, PowerBI, Microstrategy, Qlik, Elastic Stack, Oracle, entre otros (deseable) Título universitario o terciario o diplomatura en informática, ciencias de la computación, ciencia de datos, estadísticas, matemáticas u otro campo relacionado (deseable) Poseer sólidas habilidades técnicas en ingeniería de datos en la nube (GCP, AWS o AZ), incluida experiência con pipelines de datos, procesos ETL, tecnologías de big data y almacenamiento de datos (deseable)


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