Top Data Engineer Jobs in Madrid

As a Principal Database Engineer, you will architect scalable PostgreSQL solutions, ensuring data reliability, performance, and collaborating with teams to build a robust data platform for GitLab's growth.

As a Data Engineer, you'll design, develop, and implement high-performance data infrastructure and pipelines while communicating effectively with various stakeholders.

Design and optimize data infrastructure on GCP, focusing on ETL/ELT pipeline development, data governance, and ensuring high data quality while collaborating with cross-functional teams.

The role involves building AI-driven products, designing intelligent workflows, and developing data pipelines for efficient AI integration and automation.

The role involves designing end-to-end data engineering solutions, developing projects in cloud environments, mentoring engineers, and ensuring data quality and security.

You will design and develop data solutions, create ETLs using Spark, work on cloud projects, and build scalable data pipelines.

Design, build, and optimize scalable data platforms using Azure and Databricks. Responsible for developing ETL/ELT pipelines, maintaining data quality, and collaborating with analytics teams.

The Staff Data Engineer will design and develop data infrastructure and pipelines, ensuring data quality and supporting business decision-making. This role includes mentorship, collaboration with cross-functional teams, and promoting operational excellence.

As an Analytics Engineer, you will design and maintain SQL models for on-chain data, work with transformation tools, and collaborate with engineers on data pipelines.

Design and architect scalable backend services, develop robust governance systems, build SaaS solutions, and mentor junior engineers to enhance IoT platform capabilities.

As a Data Engineer, you'll design and maintain ETL pipelines, write TypeScript code, and collaborate with stakeholders to ensure data quality and performance.

The Junior Data Engineer will analyze data, design experiments, build a marketing data stack, and collaborate with teams to improve data access and insights.

Responsible for developing backend AI features, integrating machine learning models, building data pipelines, and maintaining AI services within a retail ecosystem.

Design and build scalable ETL/ELT pipelines, maintain data models and marts, enforce data quality, and collaborate with teams for data solutions.

The Staff Data Engineer will create a scalable data platform, implement data strategy, improve operational practices, and collaborate across teams.

As a Senior Data Engineer, you'll design ETL workflows, maintain cloud data platforms, ensure data quality, and leverage AI in data operations. You'll collaborate with various teams to support data needs and optimize data architecture.

As a Data Engineer at Screenverse, you'll build ETL pipelines, ensure data quality, and contribute to data strategy in a collaborative environment.

The Senior Software Engineer will develop and optimize GPU and CPU accelerated software libraries, collaborate with teams, and lead technical projects.

Lead the design and implementation of scalable cloud-based data pipelines and architectures, ensuring best practices, compliance, and data quality.

Lead the design and implementation of strategic data architecture, develop and maintain data pipelines, ensure data governance and quality, and mentor team members.

As a Data Engineer, you'll build scalable infrastructure for data processing, lead improvements, establish data governance, and mentor engineers while ensuring high data quality.

N-iX seeks a Data Engineer with MLOps experience to create scalable ML pipelines, deploy models, and contribute to best practices in data engineering and coding.

Seeking a skilled Data Engineer to design, develop, and deploy ML solutions with expertise in Python, Databricks, Snowflake, and AWS, focusing on supply chain management.

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.

Lead the design of ML pipelines, define data contracts, manage a team of engineers, and ensure production ML systems are robust and scalable.