Senior Data Engineer

🕒 July 15

🇲🇽 Mexico – Remote

⏰ Full Time

🟠 Senior

🚰 Data Engineer

👻 Ghost score 29%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Capgemini

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1967

💼 Consulting

🏥 Healthcare

📦 Logistics

Consulting • Healthcare • Logistics

Capgemini is a global leader in partnering with businesses to transform and manage their operations by harnessing the power of technology. With expertise across a wide array of industries such as aerospace, automotive, banking, and healthcare, Capgemini provides a constantly evolving portfolio of services to meet the ever-changing needs of their clients. Their offerings include cloud, cybersecurity, data and artificial intelligence, and enterprise management, among others. Capgemini also emphasizes innovation and sustainability, helping companies achieve digital transformation while promoting environmental and social responsibility. Additionally, Capgemini provides career opportunities across various levels and professions, encouraging innovation and diversity in its workforce.

📋 Description

• Diseñar, construir y mantener pipelines de datos y procesos ETL utilizando Databricks y Apache Spark • Optimizar flujos de trabajo de datos para rendimiento, escalabilidad y eficiencia de costos • Implementar arquitectura de Lakehouse de datos y gestionar la ingestión de datos desde múltiples fuentes • Colaborar con científicos de datos y analistas para habilitar análisis avanzados y cargas de trabajo de aprendizaje automático • Asegurar la calidad, gobernanza y seguridad de todos los activos de datos • Monitorizar y solucionar problemas de clústeres, trabajos y flujos de trabajo de Databricks • Integrar Databricks con servicios en la nube (AWS, Azure o GCP) y otros sistemas empresariales • Documentar procesos, estándares y mejores prácticas para la ingeniería de datos

🎯 Requirements

• Experiencia con Delta Lake y arquitectura Lakehouse • Conocimiento de Azure Data Factory (ADF) para orquestación • Exposición a CI/CD pipelines para ingeniería de datos • Experiencia con SQL y Spark SQL • Certificaciones de Azure relacionadas con la ingeniería de datos

🏖️ Benefits

• Flexibilidad en cómo, cuándo y dónde se realiza el trabajo • Oportunidades de desarrollo profesional