Top Data Engineer Jobs in Madrid

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 deploy large-scale distributed systems and high-throughput data pipelines. Lead architecture and technical initiatives, ensure performance, resilience, and SLAs, contribute production-quality code, and mentor engineers while collaborating with product and R&D leadership.

Design, build, and operate large-scale distributed systems and high-throughput data pipelines using Go and cloud-native technologies. Lead architecture, performance optimization, reliability SLAs, and code quality. Drive technical roadmap, mentor engineers, reduce technical debt, and collaborate with product and engineering teams.

Design, build, and deploy large-scale distributed systems and high-throughput data pipelines using Go and cloud-native technologies. Lead architecture decisions, ensure performance and resilience, contribute high-quality code, reduce technical debt, and mentor engineers while collaborating with product and engineering teams.

Design, build, and own large-scale distributed systems and high-throughput data pipelines. Lead architecture, improve performance and resilience, reduce technical debt, contribute code, and mentor engineers while collaborating with product and R&D.

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 and build the knowledge layer for AI agents that represent brand identity and reasoning. Develop agentic search, dynamic retrieval, and RAG systems; evaluate retrieval/reasoning architectures; translate AI research into production systems; collaborate with product and AI teams to improve user-facing outcomes.

The Junior Data Engineer will design and optimize data infrastructure on GCP, focusing on ETL/ELT pipelines and ensuring data quality, governance, and security.

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

The Renewables Measurement & Data Engineer will validate renewable measurement data, support on-site measurements, troubleshoot systems, and analyze resource potential and asset performance.

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.

The Forward Deployed Data Engineer will manage AI-automated data platform migration projects, ensuring timely delivery and communication with clients while utilizing proprietary tools.

The Senior Data Engineer develops data solutions, builds scalable data pipelines, and fosters best practices while collaborating within a multidisciplinary team.

As a Data Engineer, you'll design and deliver data products, collaborate with teams to translate requirements, and develop ETL workflows. You'll ensure data accuracy and contribute to the architecture of Fever's data ecosystem, fostering best practices.

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

Design and develop a big-data processing engine and heavy ETL pipelines (including geo-location analysis) across cloud and on-prem. Build distributed, partitioned pipeline architectures using Spark/PySpark, Scala, Airflow, Kubernetes, and cloud platforms; follow Agile, clean-code, and software design best practices while supporting deployments and client-facing interactions.

Design and maintain scalable data pipelines and platforms, lead migration from Snowflake to client service, propose improvements, drive initiatives, and collaborate with senior engineers, product/project managers, and data analysts.

Lead design and implementation of data platforms and pipelines for a large online car marketplace. Simplify and modularize tools, address technical debt, propose improvements, and collaborate with senior engineers, product and engineering managers. Work with AWS Glue/Athena, Python/PySpark, SQL, Airflow and streaming frameworks (Kafka/Firehose) on a Canadian time-zone schedule.

Own and evolve Enode's data platform and pipelines to support the Flex product: build reliable datasets, ensure data quality and monitoring, enable self-serve analytics, and partner with data science on feature pipelines and model readiness. Drive pragmatic platform improvements, documentation, and tooling to scale data reliability and trust across delivery, billing, and reporting.

Design, validate and oversee mechanical systems for data centers. Create cost-effective mechanical designs and construction documentation, coordinate with internal teams and external vendors, test installations, analyze performance, and visit sites to supervise builds and ensure quality.

Lead delivery of end-to-end data and analytics solutions: build dimensional models, develop Power BI dashboards, perform exploratory analysis, design Azure-based data pipelines, capture client requirements, run scenario modelling, test and assure solutions, prepare client communications and lead project teams.

Lead data and analytics projects: design dimensional models, build Power BI dashboards, run exploratory analysis, capture client requirements, develop end-to-end data pipelines on Azure, test and assure solutions, support client decision-making, and contribute to business generation and people development.

Build and operate large-scale data pipelines and orchestration for generative AI research, focusing on video/audio datasets, feature extraction, labeling, and dataset quality to improve model performance.

Design, build, and operate scalable data pipelines and cloud solutions, focusing on monitoring and automation while working with AWS services.

The role involves creating and automating infrastructure features for data platforms using Python, with a focus on distributed systems and collaboration within a global team.