Data Engineer: Cloud Pipelines for Automotive Innovation

Applus IDIADA; l'Albornar; Híbrido; EUR 45.000 - 65.000; Jornada completa

Descripción de la vacante

Applus IDIADA is seeking a Data Engineer to join the Digital Solutions - DataLab team in a hybrid Spain-based role. You will design, build and maintain scalable data pipelines, work with Python and SQL, and apply modern database technologies including NoSQL, vector and graph databases, and cloud solutions such as AWS.

Responsibilities include ETL development, data governance, and ensuring data quality and accessibility for data scientists and analysts.

Formación

• Proven experience in Python programming and SQL
• 2+ years of experience in data engineering projects
• Strong knowledge of database systems including relational, NoSQL, vector, and graph databases
• Experience with big data technologies
• Proficiency with cloud-based data solutions, preferably AWS
• Knowledge of data modeling and data governance principles
• Experience in designing and implementing ETL processes
• Familiarity with vector similarity search and graph data modeling is a plus

Responsabilidades

• Design, build, and maintain scalable data systems
• Create efficient ETL processes and ensure data quality
• Collaborate with data scientists and analysts to translate requirements into data architectures
• Select and implement appropriate database technologies for different use cases
• Optimize data retrieval and ensure data integrity

Conocimientos

Python

SQL

NoSQL

Vector databases

Graph databases

Big data

OTEL

Logging

AWS

Data modeling

Data governance

ETL

Educación

Degree in Computer Science, Software Engineering, Data Engineering or related field

Cloud/Data engineering certifications (advantage)

Herramientas

MongoDB

Descripción del empleo

Applus IDIADA is seeking a Data Engineer to join the Digital Solutions - DataLab team in a hybrid Spain-based role. You will design, build and maintain scalable data pipelines, work with Python and SQL, and apply modern database technologies including NoSQL, vector and graph databases, and cloud solutions such as AWS.

Responsibilities include ETL development, data governance, and ensuring data quality and accessibility for data scientists and analysts.