Top Data Engineer Jobs in Spain

Design and maintain ETL/ELT pipelines, integrate and model data, ensure data quality, and develop scalable Power BI dashboards and reports. Analyze business data, define KPIs, optimize reporting performance, and collaborate with technical and business teams. The role also explores LLM and AI capabilities in data workflows and requires strong SQL, Python, DAX, and Power Query skills.

Build and maintain data pipelines, infrastructure, data models, and automation for analytics and machine learning workflows. Collaborate with ML engineers on model training, quality assessment, and releases. Improve internal data delivery processes and enable efficient access to large-scale organizational data.

Build and maintain data pipelines and infrastructure for analytics, experimentation, and company metrics. Collaborate with machine learning engineers on training, quality assessment, and model release automation. Improve data delivery processes, automate manual workflows, and develop scalable data models. The role requires strong Apache Spark and Python expertise, SQL proficiency, Git experience, and familiarity with cloud data platforms and Kubernetes.

Create, verify, validate, and deliver Integrated Product Data for the NH90 helicopter program. Responsibilities include authoring technical documentation, managing work packages and spare-parts configuration, analyzing change triggers and service bulletins, producing material evolution tables, and creating or modifying technical illustrations. The role requires coordination across international teams and expertise in aerospace documentation standards, configuration control, technical drawings, and tools including Windchill, SAP, AMOSS, and IsoDraw.

The job description provides limited role-specific details. As a Data Engineer at Ayvens, the position likely supports data infrastructure and engineering initiatives that enable digital transformation, fleet management, sustainable mobility, and technology-enabled customer solutions.

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.

Build and manage data pipelines, ingest and transform data from diverse sources, construct modeling tables, and deliver FAIR data products. Collaborate with process experts and data scientists to curate data for advanced analytics, define secure data exchanges, map data landscapes, and maintain information security and compliance. The role requires cloud, database, ETL, software engineering, and biopharmaceutical manufacturing knowledge, with occasional global travel and possible clean-room work.

Collects and reviews fund administration data, identifies missing or inaccurate information, prepares and transmits reports to third parties, and monitors reporting activities. The role ensures timely, accurate reporting, escalates issues, manages workload priorities, and collaborates with technology teams to improve and automate reporting processes. Training is provided on data collection, report compilation, review, and transmission procedures.

Designs, develops, tests, optimizes, and maintains scalable batch and near-real-time data pipelines and architectures. Ensures data quality, builds API integrations, improves internal data processes, and supports machine learning, data science, BI, and product initiatives. The role requires experience with data warehouses, relational and NoSQL databases, data modeling, event-driven architectures, SQL, Python, Airflow, Spark, and AWS data services.

Owns the design, development, operation, and governance of data pipelines and integration patterns supporting Medical Affairs AI products. Builds APIs and ETL/ELT solutions connecting enterprise systems to analytics platforms, RAG pipelines, vector databases, and GraphRAG applications. Ensures data quality, privacy, lineage, compliance, and protection of sensitive information. Partners with architecture, engineering, product, and business stakeholders to deliver reusable, production-grade data integrations.

Build and maintain full-stack applications using Angular, TypeScript, Node.js, Express.js, and React. Design ETL pipelines and ClickHouse data models for hospitality analytics, optimize SQL queries, troubleshoot data and application issues, support users, and maintain Azure infrastructure, CI/CD pipelines, caching, and cloud integrations. Collaborate with product and analytics stakeholders while ensuring data quality, security, and clear communication with nontechnical users.

Lead Salesforce data migration activities, including data extraction, cleansing, deduplication, transformation, loading, reconciliation, and validation. Develop source-to-target mappings aligned with Salesforce’s data model, execute migrations using Data Loader, ETL tools, and APIs, and support integrations with ERP, marketing, and data platforms. Collaborate with architects, developers, and business stakeholders while ensuring data quality, integrity, and compliance with technical and business requirements.

Build unstructured-data ingestion and context-layer pipelines for an investment group. Responsibilities include historical backfills, document parsing, entity resolution, deduplication, incremental API synchronization, embeddings, vector and graph storage, access scoping, lineage, PII protection, orchestration, monitoring, cost control, and operational runbooks.

Own the data engineering side of DoiT’s integrations framework by building and maintaining third-party billing and usage API integrations. Ensure data correctness, completeness, normalization, reconciliation, and support for negotiated rates. Manage orchestration, scheduling, backfills, and pipeline operations while using AI throughout development. Collaborate with product, support, and engineering teams to expand vendor coverage and improve cloud and SaaS spend visibility.

The Data Engineer will design, build, and maintain data pipelines while collaborating with teams to provide data-driven solutions and enhance data quality.

Build and maintain reporting datasets, data pipelines, analytical data structures, and financial reporting solutions. Optimize SQL queries, data models, and report performance; support migration from Cognos to Tableau and modern BI platforms. Translate stakeholder requirements into scalable solutions, establish data quality and governance controls, and contribute to reporting architecture modernization using platforms such as Snowflake. Collaborate across business and technology teams to deliver reliable management KPIs and self-service analytics.

Build and enhance reporting solutions, data pipelines, reporting datasets, analytical data structures, and management KPI capabilities. Maintain and optimize SQL-based reporting environments, support migration from Cognos to Tableau and modern BI platforms, and contribute to Snowflake-based architecture modernization. Partner with business and technology stakeholders to translate requirements into scalable solutions while supporting data quality, governance, lineage, controls, and self-service analytics.

Own data engineering for a cloud and SaaS billing integrations platform. Build and maintain third-party billing API integrations, operate ingestion pipelines, normalize vendor data, manage orchestration and backfills, and ensure financial-grade correctness through reconciliation and quality checks. Use AI throughout the engineering workflow and collaborate with product, support, and platform teams to expand vendor coverage and improve customer cost visibility.

Develop and maintain cloud-based data platforms, scalable data pipelines, ETL workflows, anomaly detection, and optimized aggregations. Apply Data Mesh, Data Governance, and Data Lineage principles while supporting data needs across Product and Engineering. Collaborate with analysts, scientists, software engineers, and DevOps teams to build self-service data tools and modern data architecture.

Lead the evolution of Ebury’s core data platform by designing scalable cloud-based data solutions, building data transformation and dimensional modeling frameworks, and establishing data governance. The role involves working with Python, SQL, Google Cloud Platform services, and data engineering architectures to deliver reliable, high-quality data for global financial operations and cross-functional decision-making.

Investigate marketing tracking discrepancies, trace and fix end-to-end data pipelines (especially GA4/Salesforce and gclid issues), improve revenue attribution and reporting, and partner with marketing, engineering, and sales to implement reliable tracking and reporting solutions.

Lead the design, implementation, and operation of enterprise reporting and analytics platforms. Build scalable pipelines, master data structures, lakehouse and warehouse models, Power BI semantic models, dashboards, and cost-rate databases. Ensure data quality, governance, security, lineage, and auditability while supporting DevOps, deployment, monitoring, and production operations. Partner with finance, operations, and senior stakeholders to deliver trusted data products and business outcomes across complex enterprise systems.

Leads electrical design for hyperscale and mission-critical data centers across Europe. Responsibilities include managing HV/MV/LV systems, substations, utilities, consultants, permitting, project delivery, construction support, commissioning, and integrated systems testing. The role provides client-side technical leadership, reviews designs and project documents, coordinates multidisciplinary teams, manages risks and milestones, and ensures compliance with standards and operational requirements.

Lead the architecture and hands-on delivery of an Everything-as-Code data mesh, including Kafka and NiFi event streaming, Kubernetes infrastructure, Terraform and GitOps deployment, schema governance, hybrid lakehouse integration, FinOps optimization, resiliency, and distributed observability across multi-cloud and on-premises environments.

Designs, implements, deploys, and supports data integration pipelines connecting business, engineering, machine, drone, partner, customer, and government data sources. Responsibilities include defining integration tasks, managing UAT and deployments, analyzing platform performance, maintaining data-flow and configuration documentation, tracking transport metrics, and advising on integration architecture. The role requires extensive ESB and ETL/ELT experience, programming skills, database expertise, documentation abilities, and collaboration in agile project environments.