Top Data Engineer Jobs in Spain

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

The Data Engineer designs big data architecture, optimizes machine learning models, collaborates on data projects, and builds data pipelines.

As the Data Engineer, you will design and maintain data pipelines, scale data infrastructure, ensure data quality, and collaborate with analysts to enhance decision-making capabilities.

The Mid-Level Data Engineer will build and maintain data pipelines, ensuring data quality and integration for strategic revenue analysis. Close collaboration with cross-functional teams is essential.

Lead data engineering strategy and architecture for diagnostic products. Design and optimize AWS-based data platforms and PySpark, SparkSQL, and SQL workflows; improve scalability, performance, cost efficiency, security, governance, and compliance. Provide technical leadership and mentorship, enforce engineering best practices, and partner with architects, product owners, engineers, and business stakeholders. Drive GenAI and advanced analytics initiatives, including scalable data lakes and warehouses.

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

Own the financial audit data workstream for Printful and Printify. Deliver accounting reconciliations, investigate transaction discrepancies, build Snowflake transformations, extend Looker models, collaborate with Accounting and auditors, and document pipelines, corrections, and edge cases against fixed deadlines.

Design, build, and optimize scalable data systems and ETL pipelines for real-time and analytical use. Ensure data quality, integrate internal and external sources, develop internal tools, and participate across the software development lifecycle to support product, operations, and marketing needs.

Design, build, and maintain scalable data pipelines and architectures within the Microsoft ecosystem. Collaborate with data scientists and AI engineers to ensure data quality, governance, and performance for analytics, ML, and AI agents. Implement ETL/ELT, data models, CI/CD, and automation workflows using Azure, Databricks, and Power Platform tools.

Lead technical direction and hands-on implementation of semantic infrastructure for telemetry interoperability. Build scalable systems bridging OpenTelemetry, cloud and customer data models; define standards, mentor engineers, run on-call rotations, and drive cross-team platform initiatives for schema evolution and AI-enabled observability features.

Build and maintain high-performance data ingestion pipelines and features for ML models, write clean testable code, participate in code reviews and architectural decisions, monitor deployments for reliability and performance, and collaborate in an agile team following a "you build it, you run it" philosophy.

Build and maintain Databricks-based Lakehouse pipelines (batch and near-real-time) using PySpark. Design Delta Lake schemas, ensure pipeline reliability and cost efficiency, write tests, and collaborate with product and data teams to enable data enrichment and serving for internal and client products.

Design, build, and maintain ETL/ELT pipelines, model and optimize NoSQL data (MongoDB), create Metabase dashboards, prepare datasets for AI/LLM projects, support web back-end (Node.js), and collaborate with product teams to integrate AI components and ensure data quality and freshness.

Build, maintain, and improve scalable data pipelines and infrastructure to support persona modeling and reporting. Enhance system reliability with monitoring/SLI-SLO, troubleshoot reporting workflows, and collaborate across Product, DevOps, and Core Services to streamline data systems and ad delivery optimization.

Maintain and govern data tools, especially Looker, while defining data governance standards and automating data processes with LLMs, workflow tools, APIs, and MCP connections. Monitor GCP usage and costs, support conversational analytics, improve self-service data support, and identify data-consumption improvements. Collaborate with senior engineers and business stakeholders while delegating tasks and mentoring interns.

Build and maintain data infrastructure, ingestion pipelines, AWS-based processing systems, and data observability frameworks. Optimize data performance and costs, troubleshoot data quality issues, and standardize DataOps practices through version control, automated testing, and Infrastructure as Code. Collaborate with stakeholders on high-volume telemetry and clickstream data while supporting reliable downstream analytics.

Lead the design, development, testing, and deployment of scalable enterprise data pipelines and products supporting Home Buying. Provide technical leadership across architecture, governance, engineering standards, delivery coordination, and technical decision-making. Build solutions using AWS, Big Data technologies, Snowflake, and dbt; mentor engineers, support recruitment, collaborate with stakeholders, and contribute to GenAI adoption and data platform modernization.

Design and lead scalable, secure data architectures and end-to-end data flows across cloud and hybrid environments. Define standards, guide pipeline development and modeling, advise on storage, governance and performance, evaluate new tools, and lead technical initiatives across teams.

The Data Engineer will design and optimize data pipelines for AML solutions, support data scientists, and manage technical relationships with customers.

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 data pipelines and architecture, optimize machine learning models, and collaborate on data projects for international brands.

As a Data Engineer, you will model data using dbt, manage data infrastructures, design data pipelines, and deliver training and presentations to clients.

As a Technical Data Engineer, you will develop and maintain the Aircraft Maintenance Manual, ensuring compliance with specifications while managing technical documentation and process harmonization.

Develop feature stores and other data services, build EL/ELT/ETL pipelines, integrate data-processing and storage tools, and support scalable high-load systems. The role requires expertise in Python, SQL, event-driven systems, streaming pipelines, system design, APIs, message brokers, and cloud-based data technologies. It is fully remote and involves operational responsibilities within an international fintech engineering team.

Lead data engineering initiatives across large-scale e-commerce datasets. Own data models, transformation architecture, analytics projects, client data products, internal dashboards, documentation, and technical roadmap delivery. Collaborate with technical and business stakeholders, mentor teammates, and translate business needs into scalable data solutions using SQL, BigQuery, Google Cloud, ETL/ELT tools, and visualization platforms.