Stefanini LATAM
10,000+ employees
Founded 1987
🤖 Artificial Intelligence
🔒 Cybersecurity
☁️ SaaS
Artificial Intelligence • Cybersecurity • SaaS
Stefanini LATAM is a technology solutions provider with over 30 years of experience in digital transformation. The company focuses on integrating innovative technological solutions for businesses to enhance their operational models and customer experiences through automation, artificial intelligence, cybersecurity, and data analytics. Stefanini collaborates with clients to identify opportunities for optimization and growth, ensuring that businesses can adapt to the evolving digital landscape effectively.
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Stefanini LATAM
10,000+ employees
Founded 1987
🤖 Artificial Intelligence
🔒 Cybersecurity
☁️ SaaS
Artificial Intelligence • Cybersecurity • SaaS
Stefanini LATAM is a technology solutions provider with over 30 years of experience in digital transformation. The company focuses on integrating innovative technological solutions for businesses to enhance their operational models and customer experiences through automation, artificial intelligence, cybersecurity, and data analytics. Stefanini collaborates with clients to identify opportunities for optimization and growth, ensuring that businesses can adapt to the evolving digital landscape effectively.
📋 Description
• Monitorear activamente los flujos y DAGs críticos durante la franja 3:00 a.m.–12:00 p.m. • Atender incidentes P1–P5 conforme a los runbooks y directrices del Tech Lead de NEQUI • Ejecutar diagnóstico inicial: revisión de logs Airflow, métricas Grafana, estado Redshift • Gestionar trazabilidad de incidentes en Jira SM con documentación completa • Ejecutar y validar pipelines dbt y flujos AWS Glue cuando aplique • Participar en la construcción colaborativa de runbooks operativos • Mantener comunicación fluida con el DRE y el Tech Lead de NEQUI durante la operación • Participar en ceremonias de sprint (planning, review, retrospectiva)
🎯 Requirements
• 2+ años de experiencia en ingeniería de datos, DataOps o soporte de plataformas de datos • Experiencia con Apache Airflow: lectura de logs, depuración de DAGs, reactivación de tareas • Conocimiento de dbt: ejecución de modelos, interpretación de errores, pruebas de calidad • Manejo de SQL avanzado para diagnóstico en Amazon Redshift • Conocimiento de AWS Glue y Lambda para diagnóstico de pipelines ETL/ELT • Capacidad de lectura e interpretación de dashboards en Grafana • Experiencia con Jira o herramienta ITSM equivalente • Disponibilidad para trabajar en turnos rotativos incluyendo madrugada y fines de semana
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