Top Data Engineer Jobs in Spain

Build and maintain Snowflake-based data assets and metrics layers using dbt, SQL, and Python. Design reliable data models and pipelines, enable self-service analytics, collaborate with stakeholders, document definitions and best practices, and deliver scalable analytics solutions.

Lead migration from Snowflake to the client platform, build AI-native data migration capabilities, design and maintain scalable data pipelines and platforms, propose improvements, and collaborate with senior engineers, product/project managers, and data analysts.

Design, develop, and maintain a scalable data platform. Collaborate with stakeholders to deliver data solutions, enforce data governance and quality, drive innovation, and implement data warehousing, lakes, and cloud-based pipelines at scale.

Lead architecture and delivery of AI-enabled CRM, customer engagement and banker experience platforms. Drive platform strategy across cloud, APIs, workflow orchestration and AI, establish engineering standards, ensure security/privacy/responsible AI, mentor engineers, and influence stakeholders to deliver scalable, resilient customer and colleague experiences.

Lead design and delivery of scalable, cloud-native software and data/AI-enabled platforms for Business Banking. Build APIs, services and platform capabilities, drive architecture and engineering standards, mentor engineers, champion CI/CD, observability and DevSecOps, and support production platforms to deliver customer and colleague digital experiences.

Design, build, and operate high-frequency, event-driven data pipelines into Snowflake; implement reverse ETL; model data with dbt; deploy cloud infra as code; monitor and improve production reliability, latency, quality, and cost; mentor teammates and establish data engineering standards.

Build and operate scalable, secure database platform infrastructure on cloud (AWS). Implement IaC, CI/CD, container orchestration, observability, participate in on-call rotations, collaborate with product teams and deliver platform improvements.

Design and build data products on an AWS data platform using streaming and batch technologies. Create data contracts, debug pipelines and batch jobs, promote best practices, and collaborate with product teams and stakeholders to resolve data pipeline and contract issues.

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.

Design, build, and own end-to-end data pipelines on BigQuery and dbt; orchestrate workflows with Dagster; enable analytics and AI use cases; build marketing attribution and reverse-ETL; enforce data quality, observability, and platform standards.

Design, build, and own scalable data platforms across Azure, AWS, and Snowflake. Architect warehouses, semantic layers, ELT/ETL pipelines, and AI/ML data infrastructure (feature stores, vector DBs, RAG/LLM-ready). Lead standards for modeling, observability, CI/CD, automation, governance, and mentor teams while partnering cross-functionally to drive data strategy.

Build and scale a blockchain data platform handling petabytes of on-chain data. Design and implement distributed systems, data ingestion/decoding pipelines, and performant SQL processing. Write production code (Kotlin, Go, Java, Rust), improve developer experience, automate operations (including AI-driven automation), and own platform components.

As a Senior Data Engineer, you will design and maintain data pipelines, ensure data quality, and collaborate with stakeholders to deliver data solutions that drive business value while mentoring other engineers.

The Software Engineer will develop and enhance data collection and ingestion pipelines to support AI model training, focusing on cloud infrastructure and data processing.

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.

The Cloud Engineer will manage and enhance Azure Databricks environments, focusing on production readiness, pipeline reliability, automation, and collaboration with data teams to ensure robust AI and data capabilities.

As an Azure Data Platform Engineer, you design, build, and maintain scalable data solutions on Azure, focusing on infrastructure, optimization, and security in collaboration with cross-functional teams.

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.

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.

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.

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.

The Senior Data Systems Engineer will manage and operate network infrastructure in manufacturing environments, ensuring uptime and resolving complex issues. This role requires extensive hands-on experience in network engineering and support for production-critical environments.

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.

As a Senior Data Engineer, you'll build and manage data pipelines, ensure data quality, and collaborate across teams, contributing to the Data Platform's growth.