Top Data Engineer Jobs in Madrid

Own and evolve the enterprise LookML semantic layer, build scalable Looker data products, optimize performance and governance across Looker instances, translate stakeholder needs into reusable models, mentor junior developers, and support conversational analytics and AI-driven queries.

Own and evolve the core data platform: warehouse design, dbt transformations, and production AWS pipelines. Refactor and harden API-driven data flows, ensure observability and testing, partner with backend and product teams, and contribute to data-aware backend features to deliver reliable, product-focused data.

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.

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.

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.

Build and maintain high-performance, fault-tolerant distributed backend services and data pipelines for large genomic and health datasets. Design storage, indexing, and async event workflows; optimize latency, throughput, and reliability. Partner with bioinformatics and product teams to validate scientific accuracy and guard AI-driven responses.

Lead design and implementation of a cloud data platform on Azure. Build ingestion and transformation pipelines (Data Factory, Databricks), enable downstream reporting/APIs (SQL, Cosmos, Synapse), automate deployments (ARM templates, DevOps), advise on data models, integration, security, and BI, and collaborate with architects and engineers to deliver short- and long-term enterprise data solutions.

Lead design and implementation of a cloud data platform: plan milestones, build Azure Data Factory pipelines and Databricks transformations, integrate diverse data stores (SQL, Cosmos DB, Synapse), automate deployments (ARM templates, DevOps), advise on data models, APIs, security, and BI, and provide short-term solutions and best practices for enterprise data needs.

The Tableau Developer will design, build, and maintain Tableau dashboards, optimizing performance and ensuring data accuracy while collaborating with stakeholders.

Build end-to-end features for a data orchestration platform across Java/Micronaut backend and Vue 3/TypeScript frontend. Implement data-aware orchestration (assets, lineage, freshness, quality), create integrations/plugins (dbt, Fivetran, Airbyte, warehouses), improve UI (flow editor, topology, dashboards), collaborate on 8-week releases, review PRs, and engage with the open-source community.

As a Senior Data Engineer, you will deliver complex projects, manage customer relationships, and mentor junior engineers while using Databricks and various cloud platforms.

Design and build highly scalable, low-latency market data systems and APIs. Implement backend services, influence architecture, maintain test coverage, participate in code reviews, troubleshoot incidents, and occasionally be on-call. Work spans streaming and historical market data endpoints and developer-focused API improvements.

Build and own end-to-end features for Fever's native Android app: shape product with PM/Design, implement Kotlin/Compose solutions in a multi-module Gradle codebase, integrate APIs and payment SDKs, instrument experimentation/analytics, iterate from data, and bridge AI/data capabilities into the user experience.

Own and operate Databricks-based data platform production support, build and migrate ETL/ELT pipelines to Databricks across Azure/AWS, optimize compute and performance, enforce Delta Lake architecture and data security, implement observability and CI/CD, support multi-tenant onboarding and on-call incident response, and maintain runbooks and SLA metrics.

Own and evolve a GCP-native data platform from ingestion to reporting. Lead architecture, reliability, observability, data quality, cost optimization, and AI-assisted engineering practices while mentoring engineers and collaborating with product and customer teams.

Design and implement end-to-end data architecture (Postgres CDC -> Kafka -> Snowflake). Own ingestion, orchestration, transformation, streaming pipelines, and data quality. Define data contracts, tenant separation, replay/reload, and external delivery. Start hands-on and grow a small data engineering team with a 3/6/12-month roadmap.

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.

Design and maintain data infrastructure, build pipelines for data collection, ensure data quality, and collaborate with stakeholders on data requirements.