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# Data Engineer

- **Company:** Multiverse Computing
- **Location:** San Sebastián, Spain
- **Contract:** Permanent contract
- **Skills:** Amazon Web Services, Microsoft Azure, Big Data, Computer Programming, Data Architecture, Information Engineering, Extract Transform Load (ETL), Data Systems, Apache Hadoop, Python (Programming Language), Machine Learning, NoSQL, Software Engineering, SQL Databases, Cloud Platform System, Data Ingestion, Apache Spark, Database Performance, Containerization, Information Technology, Apache Kafka, Software Version Control, Data Pipelines, Docker
- **Published:** August 21, 2026
- **Apply:** https://www.jobleads.com/es/job/edbd4e13de6729358e4091d75f37adf08

## About the Role

* Bachelor's or master's degree in computer science, software engineering, or a related field.
 * 1+ year of experience or demonstrated project in data engineering or a related field.
 * Strong programming skills in Python or a similar language.
 * Expertise in data modeling, ETL development, and database management.
 * Experience with SQL and NoSQL databases.
 * Knowledge of cloud-based data platforms such as AWS, GCP, or Azure.
 * Understanding of CI/CD pipelines and version control in the context of data workflows.
 * Excellent problem-solving skills and attention to detail.
 * Strong communication and collaboration skills.

Preferred qualifications

 * Familiarity with big data technologies such as Hadoop, Spark, and Kafka.
 * Experience with containerization and orchestration tools such as Docker and Kubernetes.

## Description

As a Data Engineer, you will be responsible for designing, building, and maintaining the data architecture that underpins our organization's data systems. You will work closely with Machine Learning Engineers, Tech Managers, and other members of the technical team to ensure that our data is clean, accurate, and accessible to all stakeholders., * Develop and maintain the organization's data pipeline architecture.

 * Design and implement ETL processes to ensure that data is clean, accurate, and accessible.
 * Work closely with Machine Learning Engineers to ensure that data is properly structured for analysis and building predictive models.
 * Collaborate with cross-functional teams to identify opportunities to improve data quality and accessibility.
 * Build and maintain data pipelines to automate data ingestion and processing.
 * Manage and optimize database performance.
 * Stay up to date with emerging trends in data engineering and recommend new tools and technologies as appropriate.


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