Top Data Engineer Jobs in Spain

Design, build, and maintain scalable data pipelines and architectures within the Microsoft ecosystem. Collaborate with data scientists and AI engineers to ensure data quality, governance, and performance for analytics, ML, and AI agents. Implement ETL/ELT, data models, CI/CD, and automation workflows using Azure, Databricks, and Power Platform tools.

Design and build data pipelines, acquire and store data, transform data into insights, optimize systems, and ensure data quality while collaborating with various stakeholders.

Design, implement, and maintain data capture, processing, storage, distribution and visualization systems. Build scalable, highly available data pipelines and distributed systems on AWS. Write clean, tested code, document designs, propose architecture improvements, and work in an agile team using streaming and big-data tools.

Build and maintain high-performance data ingestion pipelines and features for ML models, write clean testable code, participate in code reviews and architectural decisions, monitor deployments for reliability and performance, and collaborate in an agile team following a "you build it, you run it" philosophy.

Design, build, and optimize scalable data systems and ETL pipelines for real-time and analytical use. Ensure data quality, integrate internal and external sources, develop internal tools, and participate across the software development lifecycle to support product, operations, and marketing needs.

Build and maintain cloud-based media data pipelines and user-facing data products. Design, deploy and govern BigQuery/DBT pipelines, APIs and dashboards, ensure data quality/security, manage vendors, and drive product-oriented delivery and adoption.

As a Senior Software Engineer, you will lead backend development for the Merchant Data Platform, mentor junior engineers, ensure system reliability, and collaborate in product development. Your role involves project management, technical planning, and maintaining high availability of services.

Build the companys first data stack and data products (internal analytics and customer-facing). Work across data engineering, devops, and software tasks; ship early features, improve developer experience, document proposals, and iterate based on feedback.

Design, build, and scale ETL/ELT and real-time data pipelines for AI workloads (RAG, fine-tuning, batch inference). Transform unstructured data into vectorized formats, manage feature stores and vector databases, enforce data quality/governance, integrate event systems (Kafka), and collaborate with ML and engineering teams.

Build, maintain, and optimize ETL pipelines and analytical data warehouse environments. Deploy, monitor, and scale machine learning models in production; automate model deployment and recurring data processes. Collaborate with Data Science, Engineering, BI, Risk, and IT teams; troubleshoot performance issues and maintain technical documentation.

Entry-level Data Engineer internship supporting database management, data integration, quality, and maintenance. Provide reliable, structured data to analysts, resolve incidents, and support database structuring and operations.

The Data Engineer will design data pipelines and architecture, optimize machine learning models, and collaborate on data projects for international brands.

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

As a Technical Data Engineer, you will develop and maintain the Aircraft Maintenance Manual, ensuring compliance with specifications while managing technical documentation and process harmonization.

The Data Engineer will design and optimize data pipelines for AML solutions, support data scientists, and manage technical relationships with customers.

Embed with customers to design, prototype, deploy, and optimize production AI solutions. Own delivery workstreams, build RAG and agentic systems, ensure scalability, reliability, and knowledge capture, and contribute to platform improvements.

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

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

Design, build, and maintain cloud 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 environments, and collaborate with BI teams for reporting and analytics.

Design, develop, and maintain Azure Databricks-based data pipelines and Lakehouse architectures using PySpark, Spark SQL, Delta Lake, and Azure Data Factory. Integrate diverse sources into SQL Server-based warehouses, ensure performance and data quality, and support BI/reporting (Power BI) and cloud migration efforts.

Design, build, and maintain cloud data pipelines and Lakehouse architectures using Azure Databricks, PySpark, Delta Lake, and Azure Data Factory. Integrate and transform large datasets, optimize performance, support SQL Server/SSIS environments, and collaborate with BI teams to enable analytics and reporting.

Design, develop, and maintain Azure Databricks data pipelines and Lakehouse architectures using PySpark, Spark SQL, Delta Lake, and Azure Data Factory. Integrate data from multiple sources into SQL Server-based warehouses, ensure scalability, performance, and data quality, support BI reporting, and evolve cloud-based data platform architectures.

The Data Engineer will design, develop, and maintain scalable data systems and pipelines, manage cloud infrastructure, and collaborate on data-driven decision-making processes.

Design and maintain ETL/ELT pipelines on Google Cloud Platform, optimize data processing workflows, and collaborate with stakeholders to develop data solutions.

The Data Engineer will design and maintain data models, develop BI solutions, integrate data, and optimize data flows while collaborating with stakeholders.