Top Data Engineer Jobs in Spain

As a Data Engineer, you will enhance data governance and integration processes, maintain data pipelines, and support data-related needs for analytics and product teams.

Lead design and implementation of scalable data models and ETL/ELT pipelines using Python. Build analytics-ready datasets, optimize database performance, enforce data governance, improve observability, and lead engineering teams to deliver a reliable data platform aligned with business needs.

Design and build scalable ETL/ELT and feature pipelines for image and metadata ingestion, maintain ground-truth datasets, enable reproducible model training and deployment, and collaborate with data scientists and engineers to deliver production-grade image recognition solutions that drive quick-commerce product growth.

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.

Design, build, and maintain ETL pipelines, data warehouses, and data models; integrate and monitor data sources; ensure data quality and lineage; collaborate with Data & Analytics stakeholders and provide documentation and training.

Design, build, and maintain scalable data pipelines and ETL processes using Databricks, Spark, Delta Lake and BigQuery across multi-cloud environments. Optimize and monitor pipeline performance, implement security and testing practices, document infrastructure, and collaborate with stakeholders and data teams.

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 Data Engineer, you'll design and maintain data pipelines, ensure data quality and reliability, and support product engineering teams in leveraging the Data Platform.

Lead the development of data and AI products, translating business needs into technical specifications and managing the product roadmap and backlog priorities.

The Data Engineer will design and build data pipelines, develop database solutions, create data algorithms, optimize systems, ensure data quality, and collaborate with other teams.

Lead product roadmap and delivery for data engineering and AI components, translate business needs into technical requirements, prioritize backlog, run agile ceremonies, collaborate with engineers and AI scientists, monitor performance and data quality, and engage stakeholders to improve platform features.

As a Senior Clinical Data Science Programmer, you will design and implement data pipelines, ensuring data integrity and collaboration with various users in a fully remote environment.

As a Data Engineer, you'll build and maintain data pipelines, collaborate with stakeholders, and establish data governance and quality standards to empower data-driven decision making at Bitpanda.

As a Data Engineer, you will enhance data models, optimize performance, design data architectures, and develop high-performance ELT pipelines to drive business insights.

The Azure Databricks Data Engineer/Architect will design, build, and optimize data platforms on Azure, focusing on ETL/ELT pipelines, data quality, governance frameworks, and collaboration with analytics and ML teams.

Design, develop, and implement data solutions using Microsoft technologies, create data pipelines with Python and SQL, and apply DevOps practices.

The Principal Vector Data Engineer will design and implement vector embedding models for multimodal biomedical data processing, develop quality control protocols, and contribute to digital biomarker identification. The role involves collaboration with cross-functional teams to advance machine learning applications in neurodegenerative disorders.

As a Data Engineer, you will design, build, and maintain data pipelines, ensure data quality, and collaborate with stakeholders to deliver data solutions.

Design, build and maintain scalable Spark/PySpark and SQL pipelines on Databricks. Implement Medallion Architecture, Delta Lake, Unity Catalog governance, data-quality monitoring, orchestration (Airflow), and performance optimisations.

Design, build, and operate production-grade data pipelines and curated datasets on AWS. Implement near-real-time ingestion (CDC), BI-ready data models, ETL/ELT in Python (Polars), data quality and observability, and orchestration with Airflow/AWS tools.

As a Principal Database Engineer, you will architect scalable PostgreSQL solutions, ensuring data reliability, performance, and collaborating with teams to build a robust data platform for GitLab's growth.

The Data Engineer will build and maintain data acquisition systems, ETL pipelines, and APIs for market intelligence, focusing on automotive data. Collaboration with various teams to ensure data quality and insights is key.

Design, build, and optimize ETL/ELT pipelines, ensure data quality, and collaborate with teams to deliver scalable data solutions.

Partner with Product and Marketing to design and maintain ETL/ELT pipelines and data models, integrate MarTech systems, enable end-to-end funnel traceability and attribution, process UX clickstream data, and apply engineering best practices to deliver reliable, real-time customer insights.

Design, build, and own scalable ETL/ELT data pipelines (Snowflake, Dagster, dbt). Migrate legacy Django/Celery pipelines, ensure data quality, observability, and collaborate with Product, Analytics, and Data Science.