Top Data Engineer Jobs in Madrid

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.

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.

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.

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

Build and maintain scalable data pipelines, transformations, and analytics-ready models using dbt, SQL, Python, and Snowflake. Implement ingestion, CDC, API integrations, testing, monitoring, and observability. Collaborate with analysts and stakeholders to define metrics, ensure data governance and compliance, and optimize data platform reliability.

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 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.

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.

Own and scale the ingestion pipeline and backend abstractions for high-throughput AI tracing data. Optimize ClickHouse schemas and queries, operate Langfuse Cloud and self-hosted deployments, and build infrastructure-heavy features that enable product engineers to ship data-heavy capabilities.

Lead design and implementation of scalable, real-time data infrastructure. Build and optimize production-grade streaming pipelines, employ spec-driven development and agentic AI workflows, implement testing/monitoring, take ownership of systems, and mentor junior engineers.

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

Design, build, and own streaming data pipelines and feature stores to enable low-latency inference and real-time model serving. Partner with ML and infra teams to define data contracts, ensure data quality, observability, and SLAs, and move batch pipelines toward real-time production. Evaluate streaming and feature store technologies and contribute to inference pipeline tooling.

Build and maintain real-time streaming data pipelines and feature stores to power low-latency model inference. Collaborate with ML and AI infra teams on data contracts, observability, and SLAs; drive batch-to-real-time migrations and evaluate emerging streaming/feature store technologies.

Seeking a Senior Data Support Engineer with 5-6 years of experience in Data Engineering, specifically utilizing Snowflake, Python, SQL, and AWS for data manipulation, warehousing, and testing processes.

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 and develop cloud-native backend services in Rust to process terabytes of data daily. Build and operate data-intensive microservices on AWS and Kubernetes, integrate with distributed databases and messaging systems (Kafka/RabbitMQ), and collaborate across teams to deliver observability features.

The Principal Customer Data Platform Engineer will manage the customer data architecture, focusing on tracking, identity resolution, compliance, and data governance for Airalo. They'll collaborate with cross-functional teams to ensure systematic data flow, integrity, and compliance across various platforms and lead architectural decisions.

The Senior Data Engineer will lead the design and evolution of scalable data architectures, mentor team members, build data pipelines, and integrate Generative AI into workflows.

As a Senior Software Engineer, you'll design and build scalable market data systems, improve API architecture, and enhance overall system performance, contributing to Alpaca's infrastructure for trading financial assets.

Design, develop, and maintain scalable backend services and APIs; manage and serve ML models in production (MLOps); ensure performance, security, and high availability; optimize databases; implement authentication/authorization; write tests; monitor with observability tools; collaborate across teams and maintain technical documentation.

The Senior Data Platform Engineer will lead project delivery for data infrastructure, manage near real-time services, and collaborate across teams while contributing to AI and data governance frameworks.