Ingeniero de Datos
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Job Description
Data Engineer designing and operating data solutions for banking clients at Keppri. Collaborating with teams to ensure data quality and governance in financial environments.
Responsibilities:
- Diseñar y desarrollar pipelines ETL/ELT (batch y/o streaming) para ingestión, transformación y publicación de datos
- Implementar y mantener modelos de datos en data lake / data warehouse (modelos dimensionales, data marts, capas bronze/silver/gold)
- Optimizar performance de consultas y procesos (particionado, clustering, manejo eficiente de archivos/tablas)
- Asegurar calidad de datos (validaciones, reconciliaciones, reglas de negocio, monitoreo de pipelines)
- Implementar linaje, catálogo y documentación de datasets, definiendo estándares de nombres y metadatos
- Gestionar accesos y seguridad de datos (principio de mínimo privilegio, cifrado, clasificación de datos sensibles)
- Monitorear pipelines y plataformas, gestionar incidentes y establecer SLAs/controles operativos
- Automatizar despliegues con CI/CD e Infraestructura como Código cuando aplique
- Levantar requerimientos con áreas de negocio (canales, riesgo, finanzas, operaciones) y traducirlos a soluciones de datos
- Colaborar con analistas/DS/BI para habilitar datasets confiables y reutilizables
Requirements:
- +3 a 5 años de experiencia en ingeniería de datos en entornos productivos
- Experiencia comprobada en sector bancario/financiero (datos transaccionales, auditoría, calidad, trazabilidad)
- Dominio de SQL avanzado (optimización, ventanas, CTEs, modelado)
- Experiencia con al menos una tecnología de procesamiento: Spark / PySpark (deseable fuerte) o Python para procesamiento (pandas) en pipelines orquestados
- Experiencia con herramientas de orquestación: Airflow, Prefect, Dagster u otras
- Manejo de data warehouse/lakehouse: Snowflake, BigQuery, Redshift, Databricks, Synapse (según stack)
- Conocimiento de formatos y almacenamiento: Parquet/ORC, particionado, compresión (Deseable) Delta Lake / Iceberg / Hudi
- Experiencia con control de versiones Git y prácticas de entrega continua (CI/CD deseable)
- Buenas prácticas de seguridad y gobierno de datos
- Deseables (no excluyentes) Streaming y mensajería: Kafka/Kinesis/PubSub
- Nube (ideal AWS): S3, Glue, Athena, EMR, Redshift, Lake Formation (o equivalentes)
- Data quality frameworks: Great Expectations, Deequ u otros
- Conocimiento de regulaciones/procesos bancarios: conciliaciones, riesgo, AML/KYC, reportes, auditoría
- Experiencia con herramientas de catálogo/linaje: DataHub, Collibra, Amundsen, OpenMetadata
- Modelado orientado a analítica: Kimball, Data Vault (deseable)
Benefits:
- Salario competitivo acorde a tu experiencia
- Desarrollo profesional : apoyo para formación continua y certificaciones
- Bonificaciones por desempeño
- Un ambiente centrado en tu crecimiento humano y profesional
- Proyectos retadores con impacto real en banca y transformación digital
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