{"id":1766641,"url":"https://alion.io/job/kibernum-data-engineer","title":"Data Engineer","company":{"id":61370,"name":"Kibernum","domain":"kibernum.com","url":"https://alion.io/company/kibernum","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"junior","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"inferred_city","remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":["Las Condes, Chile"],"countries":["CL"],"hiring_countries":["CL"],"hiring_countries_total":1,"salary":null,"salary_estimate":null,"experience_years_min":2,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWS","optional":false},{"name":"AWS Glue","optional":false},{"name":"AWS Lambda","optional":false},{"name":"Azure Data Factory","optional":false},{"name":"CI/CD","optional":false},{"name":"DynamoDB","optional":false},{"name":"Git","optional":false},{"name":"GitHub","optional":false},{"name":"GitLab","optional":false},{"name":"Node JS","optional":false},{"name":"PostgreSQL","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Redis","optional":false},{"name":"SQL","optional":false},{"name":"SSIS","optional":false},{"name":"JavaScript","optional":true},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-09-28T10:29:04Z","employer_posted_date":null,"last_verified_at":"2026-09-28T10:29:04Z","board_verified":false,"closed_at":null,"days_open":14,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":14},"description":"En Kibernum estamos en búsqueda de un/a Data Engineer para incorporarse a nuestro cliente del sector bancario. Será responsable de diseñar, desarrollar, implementar y mantener Data Pipelines que aseguren el flujo eficiente de datos, desde la ingesta y almacenamiento hasta el procesamiento en Batch y Real Time. Trabajarás en un entorno colaborativo, con tecnologías Cloud y enfoque en la calidad y disponibilidad de la información para la toma de decisiones.\n\nResponsabilidades: Diseñar, desarrollar y mantener procesos de ingesta, transformación y almacenamiento de datos en entornos Cloud (AWS). Implementar Data Pipelines para cargas Batch y Streaming en AWS. Administrar y mantener el Data Lake, asegurando calidad, integridad y seguridad de los datos. Desarrollar soluciones de procesamiento en Python / PySpark con librerías asociadas. Utilizar herramientas y servicios de integración de datos según la nube utilizada (AWS Glue, AWS DMS, Lambda, DataSync, etc.). Gestionar bases de datos relacionales (SQL Server, PostgreSQL) y NoSQL (Redis, DynamoDB). Trabajar con sistemas de control de versiones basados en Git (GitLab, GitHub). Colaborar con equipos de tecnología y negocio para garantizar el acceso oportuno a la información.\n\nRequisitos: +2 años de experiencia como Data Engineer. Experiencia en plataformas de datos Cloud (AWS). Experiencia en desarrollo con Python / PySpark y manejo de librerías. Experiencia en ingesta y procesamiento de datos en entornos Cloud (AWS) y On-Premise. Conocimientos en herramientas de integración y tratamiento de datos (AWS Glue, DMS, SSIS, Data Factory). Conocimientos avanzados en bases de datos relacionales (SQLServer, PostgreSQL) y NoSQL (Redis, DynamoDB). Experiencia con CI/CD y control de versiones. Ideal: experiencia en Node.js y/o .\n\nNET.\n\nDeseable: Certificación en Cloud AWS.\n\n¿Qué ofrecemos? Contrato indefinido por Kibernum. Modalidad 100% remota. 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