Especialista en Ingeniería de Datos
Code 2529.B
This role has no official English translation yet; it is shown in Spanish.
El Ingeniero de Datos cuenta con las habilidades necesarias para el gobierno y organización de los datos de una compañía para posteriores trabajos de inteligencia de negocios, análisis y ciencia de datos. Dentro de las actividades que realiza, se encuentra el diseño de modelos de datos, implementación de data warehouses y data lakes, automatización de pipelines de datos, preparación y limpieza de datos, y trabajo con altos volúmenes de datos.
Essential skills
Knowledge
- Apache Airflow
- Apache Airflow
- Apache Kafka
- Data Lake
- Ecosistemas Big Data
- Flask
- GIT
- Hadoop
- MongoDB en NoSQL
- Métodos de evaluación de riesgos de privacidad
- Métodos de visualización y exploración de datos
- NoSQL
- Paradigma MapReduce
- Proceso ASUM-DM
- Proceso CRISP-DM
- Python (computer programming)
- SPARK
- SQL
- Scikit-learn
- Sistemas de control centralizados y distribuidos
- Sistemas de control de versiones
- Spark Core
- Spark SQL
- Spark Streaming
- Tensorflow
- algorithms
- data warehouse
- software anomalies
- database
- information governance compliance
- object-oriented modelling
- statistics
- data mining
- tools for software configuration management
- distributed computing
- ICT project management methodologies
- principles of artificial intelligence
- database management systems
- integrated development environment software
- cloud technologies
- visual presentation techniques
Skills and competences
- Administrar el flujo de trabajo con GitHub
- Configurar un GIT
- Crear gráfico acíclico dirigido
- Evaluar de modelos predictivos
- Gestionar ramas de código abierto
- Gestionar repositorios remotos
- Implementar Apache Spark en la nube
- Realizar análisis exploratorio
- define database physical structure
- develop data processing applications
- establish data processes
- manage ICT data architecture
- manage database
- manage changes in ICT system
- manage data
- integrate ICT data
- normalise data
- deliver visual presentation of data
- perform data cleansing
- utilise machine learning
- use software libraries
- use scripting programming
- use object-oriented programming
- use software for data preservation
Transversal competences
- apply statistical analysis techniques
- implement data warehousing techniques
- build predictive models
- develop ICT workflow
- data quality assessment
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What to assess for this role
Technical knowledge can be verified with tests and references. What never shows up on a CV are the transversal competences, and they explain most failed hires. Before closing, it pays to measure them with a standardised battery.
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Sources
This service uses the ESCO classification of the European Commission and the Mapha Taxonomy developed by OTIC SOFOFA (CC BY 4.0), in an adapted version. Group codes come from the ILO's ISCO-08. See sources and licences