Data Engineer

A Data Engineer builds and manages complex infrastructures for data collection, storage and processing. Its main role is to ensure the availability and quality of data required for analysis and the development of business intelligence solutions.

The Data Engineer deals with large-scale data flows, working with relational and NoSQL databases, distributed storage systems, and technologies such as Hadoop, Spark or Kafka. He typically works closely with Data Scientists and Data Analysts to build efficient data pipelines that enable the extraction of valuable business insights.

The Data Engineer designs data architecture, develops ETL (Extract, Transform, Load) processes and ensures that data is structured and accessible to analysis teams. An essential component of his work is optimizing the performance and scalability of the data infrastructure to be able to handle large volumes of data (Big Data) and to support the increasingly complex requirements of different fields.

The technical skills required for this role include knowledge of programming languages ​​such as Python, Java or Scala, experience working with SQL and cloud computing technologies (AWS, Azure, Google Cloud). A Data Engineer must also be familiar with DevOps practices such as automating and monitoring systems to ensure a steady and error-free flow of data.

The Data Engineer is crucial within any data-driven organization, ensuring the right data is delivered at the right time to support strategic decisions.