Top Data Engineer Jobs in Barcelona

Lead technical data strategy and architecture for Navify Cervical Screening. Drive data integration, governance, and large-scale pipeline design; mentor engineers; evaluate new technologies; ensure compliance, quality, and timely delivery of data requirements across cross-functional teams.

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.

Design and build production-ready end-to-end data pipelines, refactor Airflow orchestration, implement data contracts and quality controls, enable domain-oriented data products, embed lineage/observability, and collaborate with architects, DataOps, BI, and engineering teams to evolve a self-service cloud data platform.

Build and maintain scalable, secure database platform infrastructure on cloud; apply IaC, container orchestration, CI/CD, observability, and networking/security best practices; collaborate with product and analytics, run on-call rotations, and deliver infrastructure and data platform improvements.

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.

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.

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.

Design, build, and maintain scalable data architecture and ETL pipelines; ensure data quality, governance, and availability; implement data models for analytics and AI/ML; collaborate with Product and Engineering; document processes and support AI development workflows.

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

The Data Engineer will build scalable infrastructure for data analysis, ensuring high performance and compliance with data protection standards while collaborating with cross-functional teams.

As a Data Engineer at Veeva, you will design and maintain data pipelines, manage healthcare data relationships, and embrace AI technologies to enhance productivity.

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.

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.

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.

Lead foundational data-engineering work to validate and re-engineer pipelines for an anonymized, centralized credit data lake. Harmonize schemas across entities, build dbt models and tests, implement data-quality suites (Great Expectations), entity resolution, anonymization controls, optimize Spark/Glue jobs, orchestrate pipelines (Airflow/Step Functions), and produce documented, feature-ready datasets and runbooks for a regulated UK/Ireland lending environment.

Own end-to-end AI-automated data platform migration projects (1-4 concurrently): scope, plan, execute, and hand off. Act as primary customer contact, configure Datafold's Migration Agent, partner with engineering on execution, and help refine delivery playbooks.

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.

Design and maintain a governed, canonical customer dataset by unifying GTM sources, building enrichment and entity-resolution pipelines, preparing structured and unstructured data for LLM/embedding workflows, implementing monitoring and lineage, and defining standards for AI-ready data across RevTech.

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