Top Data Engineer Jobs in Spain

Design and implement backend systems for data science features, build high-volume data pipelines, and ensure scalability for data-driven product capabilities.

The Data Engineer will design and build ETL pipelines for image data, work with Data Scientists on model training, and manage the infrastructure for ML models.

The Data Engineer will develop ETL/ELT pipelines, maintain Azure Databricks, integrate data sources, and support analytics by delivering reliable datasets.

As a Cloud Data Engineer, you will process complex datasets using Python and SQL, optimize ETL workflows on Azure/AWS, and build data visualizations in Power BI to support business decision-making.

As a Data Engineer, you'll design and maintain ETL pipelines, write TypeScript code, and collaborate with stakeholders to ensure data quality and performance.

The Digital Data Engineer is responsible for developing data pipelines, optimizing ETL processes, collaborating on data architecture, and maintaining documentation in an Agile environment, while ensuring data quality and integration with SAP systems.

The Data Engineer will design, develop, and maintain data pipelines for efficient data handling, working with cross-functional teams in the pharmaceutical industry.

As a Data Engineer at Ogury, you will organize and maintain data stacks, optimize reporting systems, and collaborate with teams to enhance data accessibility and insights.

As a Data Engineer, you'll maintain and configure the Snowflake data platform, design integration pipelines, and innovate with new tools. Your role supports data security and performance while collaborating across teams.

The Junior Data Engineer will analyze data, design experiments, build a marketing data stack, and collaborate with teams to improve data access and insights.

The Data Engineer will support the design and maintenance of data pipelines, collaborate with teams for data solutions, and ensure data quality in AI applications.

As a Senior Data Engineer, you'll build and optimize data pipelines for an AI platform, ensuring data integrity and performance while collaborating with various teams.

Responsible for developing backend AI features, integrating machine learning models, building data pipelines, and maintaining AI services within a retail ecosystem.

Design and build scalable ETL/ELT pipelines, maintain data models and marts, enforce data quality, and collaborate with teams for data solutions.

The Principal Data Engineer will improve data pipeline architecture, optimize data flows, and support data projects for various teams in the company.

As a Middle Data Engineer, you will migrate legacy SQL Server data to a cloud-based Snowflake system, refactor ETL processes, and ensure efficient data movement for analytics, collaborating with cross-functional teams throughout the project.

The Junior Data Engineer will develop, automate, and maintain ETL processes and data pipelines on AWS, while ensuring data reliability and scalability.

The Data Engineer will design and develop data integration pipelines using Azure technologies, ensure optimal data delivery, and collaborate across teams for data solutions.

As a Data Engineer at Screenverse, you'll build ETL pipelines, ensure data quality, and contribute to data strategy in a collaborative environment.

You will design, build, and maintain data pipelines and ETL workflows for perception models, manage dataset versioning, and collaborate with ML engineers to provide validated datasets.

As a Middle Data Engineer, migrate SQL Server data warehouses to Snowflake, refactor ETL processes, build data pipelines, and ensure reliable data movement.

You will model data as an Analytics Engineer, manage data warehouses, design data models, and deliver technical presentations to clients.

As a Data Engineer, you'll build scalable infrastructure for data processing, lead improvements, establish data governance, and mentor engineers while ensuring high data quality.

Design and implement data pipelines, develop data models, collaborate with stakeholders, optimize data integration, and ensure data quality.

Lead the development and implementation of scalable data solutions, mentor engineers, and engage with stakeholders to optimize data systems.