Top Data Engineer Jobs in Spain

The Data Engineer II will develop and optimize data platforms, build scalable pipelines, enhance existing workflows, and collaborate with teams for data solutions.

The Senior Data Engineer will design and implement data infrastructure, lead on data models, and ensure scalability, automation, and data governance in collaboration with teams.

Design, build, and maintain cloud data pipelines and Lakehouse architectures using Azure Databricks, PySpark, Delta Lake, and Azure Data Factory. Integrate sources into analytics layers, optimize performance and scalability, support SQL Server/SSIS platforms, and collaborate with BI teams for reporting and Power BI support.

Design, develop, and maintain scalable data pipelines and Lakehouse architectures using Azure Databricks, PySpark, Delta Lake, and Azure Data Factory. Integrate multiple data sources, optimize large-scale Spark processing, support SQL Server/SSIS environments, and collaborate with BI teams to enable analytics and reporting (Power BI). Contribute to cloud migration and platform evolution.

Design, build, and maintain scalable data pipelines and Lakehouse architectures using Azure Databricks, PySpark, Delta Lake, and Azure Data Factory. Integrate multiple data sources, optimize large-scale processing for performance and quality, support SQL Server/SSIS environments, and collaborate with BI teams to enable analytics and reporting.

Design, build, and maintain scalable data pipelines and Lakehouse architectures using Azure Databricks, PySpark, Delta Lake, and Azure Data Factory; integrate and optimize data from multiple sources, support SQL Server/SSIS platforms, ensure data quality and performance, and collaborate with BI teams for analytics and Power BI reporting.

Design, build, and maintain scalable data pipelines and Lakehouse architectures using Azure Databricks, PySpark, Delta Lake, and Azure Data Factory. Integrate multiple data sources, optimize performance for large datasets, support SQL Server/SSIS platforms, and collaborate with BI teams for analytics and Power BI reporting.

Design, develop, and maintain scalable data pipelines and Lakehouse architectures using Azure Databricks, PySpark, Delta Lake, and Azure Data Factory. Integrate multiple data sources, optimize large-scale processing, support SQL Server/SSIS platforms, and collaborate with BI teams to enable analytics and reporting.

Design, build, and maintain scalable data pipelines and Lakehouse architectures using Azure Databricks, PySpark, Delta Lake, and Azure Data Factory. Integrate multiple sources, optimize large-scale ETL/ELT processes, support SQL Server/SSIS environments, ensure data quality and performance, and collaborate with BI teams for reporting and analytics.

Build and maintain scalable data pipelines, transformations, and analytics-ready models using dbt, SQL, Python, and Snowflake. Implement ingestion, CDC, API integrations, testing, monitoring, and observability. Collaborate with analysts and stakeholders to define metrics, ensure data governance and compliance, and optimize data platform reliability.

Lead the development and optimization of data infrastructure for AI initiatives, collaborate with teams to architect, implement, and maintain data solutions for next-generation AI systems.

Build and own Python ML data pipelines, feature store design, and model serving infrastructure. Implement data quality and drift detection, establish reusable pipeline patterns, and operate production data systems to support ML training and inference.

The Data Engineer will design, build, and maintain data pipelines and infrastructure for analytics, ensuring data quality and collaboration with stakeholders.

As a Data Engineer, you'll design, build, and maintain ETL/ELT pipelines, optimize data workflows, and support junior engineers while working in an agile environment on AI products.

The Senior Product Data Engineer will build, iterate, and launch data products, focusing on large-scale data processing and ETL/ELT pipelines, using various technologies and implementing AI features.

Design, build, and maintain a petabyte-scale market data lakehouse: capture/normalize exchange and vendor feeds, reconstruct order books, build batch/stream pipelines, manage Iceberg-over-S3 storage, develop tooling/SDKs, and ensure reliability/observability for research and trading.

As a Data Engineer, you will model data using dbt, manage data infrastructures, design data pipelines, and deliver training and presentations to clients.

Own and build domain data warehouses and semantic layers; design, test and deploy robust data models; orchestrate pipelines with Airflow; partner with product and engineering to deliver trustworthy data products and monitoring/alerting frameworks.

The Data Engineer will design and maintain scalable data pipelines, optimize data infrastructure, monitor data quality, and enable analytics capabilities, ensuring alignment with business goals.

Design, build, and operate enterprise reporting and analytics platforms. Create scalable ELT/ETL pipelines, master data foundations, and lakehouse/warehouse semantic models. Deliver Power BI datasets and dashboards, implement data quality, governance, DevOps practices, and cost-management data solutions. Partner with finance and stakeholders and provide technical leadership across architecture, deployment, and run-state support.

Design, build, and maintain scalable data ingestion and transformation pipelines handling massive hotel data (100TB/day). Improve architecture, reliability, observability, and automation; troubleshoot live integrations and collaborate with product, engineering, and stakeholders.

As a Data Analyst, you will analyze data for business insights, create dashboards, and collaborate with teams to optimize user experience.

Lead design and ownership of Preply's data lake and end-to-end batch and streaming ingestion pipelines. Define data contracts, implement validation and observability, build enrichment and lifecycle management, enforce governance and privacy, and enable self-service ingestion templates and tooling while driving cross-team collaboration and platform reliability.

Build and improve Veeva Link's next-gen data platform and pipelines, focusing on Spark-based processing. Own features end-to-end, apply SOLID principles, add monitoring/observability, collaborate with data scientists to operate ML models, and optimize precision, recall, and cost.

The Senior Data Engineer designs and implements data infrastructure, oversees data pipelines, and ensures data reliability while mentoring junior staff. Responsibilities include automating governance, optimizing data performance, and collaborating with various stakeholders.