Top Data Engineer Jobs in Barcelona

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.

The Data Engineer will focus on data migration, building scalable pipelines, data modeling, troubleshooting, and collaborating with teams effectively.

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

The Staff Data Engineer will design and develop data infrastructure and pipelines, ensuring data quality and supporting business decision-making. This role includes mentorship, collaboration with cross-functional teams, and promoting operational excellence.

As a Middle Data Engineer, you will build and optimize data transformations and pipelines, ensuring data quality and reliability while collaborating across teams.

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.

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.

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.

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

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.

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

Design, build, and maintain scalable cloud data pipelines and analytics solutions. Implement CI/CD and infrastructure-as-code, ensure reliable data flows to the warehouse, optimize data models and performance, and collaborate across teams to embed business logic enabling data-driven decisions.

The Data Engineer will design and maintain data pipelines and models, ensuring data quality and accessibility for business decisions.

Design and implement data pipelines, manage access controls in Snowflake, and ensure compliance through automation. Collaborate with cross-functional teams to optimize data workflows.

As a Data Engineer, you'll build and optimize data pipelines, ensure data quality, and collaborate with cross-functional teams to support analytics.

Design, build, and optimize end-to-end BI and analytics data solutions. Develop and maintain Snowflake-based pipelines, implement transformations/procedures/tasks, optimize SQL and data models, expose data to Power BI, define KPIs/semantic models, document architectures, and collaborate with stakeholders in Agile/Scrum.

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.

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.

The Data Analytics Engineer will enhance data infrastructure, build reliable data pipelines, ensure data quality, and collaborate with teams to meet business analytics needs.

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.