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Data Software Engineer
Build and maintain the data platform that powers high-volume gaming services, using Java/Python, Kafka, Spark/Flink, and DevOps practices to ensure reliable ingestion, transformation, and data quality.
Senior Data Engineer | Databricks y Azure Data Factory
Design and build scalable data pipelines using Databricks, Azure Data Factory, Spark, Delta Lake and MongoDB to transform raw data into business insights for enterprise clients.
Senior Data Engineer & Tech Lead — Cloud Data Architect
Lead cloud and on-premise data projects using PySpark, SparkSQL, and Python, designing scalable data architectures and optimizing SQL/NoSQL systems for international clients.
Streaming Data Engineer — Kafka & Flink (Hybrid, Flexible)
Designs and builds real-time data pipelines using Apache Kafka and Flink, optimizing performance for streaming workloads.
Senior Data Engineer Madrid
Senior Data Engineer builds and optimizes cloud-based data pipelines using PySpark, SQL, and cloud services (Azure, AWS, GCP) to deliver scalable analytics solutions for enterprise clients.
Lead Data Engineer (Snowflake)
Lead a small team building and maintaining scalable data pipelines in Snowflake, Python, and SQL to turn raw business data into analytics-ready assets for BI and enterprise reporting.
Data Engineer – Vulnerability Data Platform (Hybrid)
Builds and maintains a distributed data pipeline that cleans, transforms, and serves vulnerability and exposure data in near real time using PySpark, Airflow, dbt, and AWS.
Data Engineer – Streaming (Kafka & Flink)
Builds real-time data pipelines using Kafka and Flink for a banking client, focusing on low-latency streaming transformations and schema governance in a critical environment.
Prácticas Data Architect | Data Engineer
Build and maintain data pipelines, clean and transform datasets, and integrate data flows into backend services and dashboards using Python, SQL, and orchestration tools.
Data Engineer (Graduate Program) (Barcelona)
Build and maintain databases, integrate data sources, and ensure analysts have clean, reliable data for insights using SQL, NoSQL, and Python.
Senior Data Engineer | Data Ops
Senior Data Engineer builds and maintains secure, scalable data pipelines for AI-driven ECG analysis in a healthtech startup, ensuring data quality and regulatory compliance.
Principal Data Engineer / Data Lead
Lead the architecture and delivery of large-scale healthcare data pipelines and platforms for Roche’s digital cervical screening solution, using Python, SQL, Spark, and cloud data tools.
Data Engineer – Clinical Trials
Build and maintain scalable data pipelines and ML systems for clinical trials, turning raw data into production-grade solutions that support trial design, patient recruitment, and real-time monitoring.
Data Engineer (Microsoft Fabric)
Build and maintain scalable data pipelines using Microsoft Fabric to integrate and optimize data from ERP, CRM, and APIs for analytics and reporting.
Data Engineer. Sector Defensa
Build and maintain robust data pipelines for a cyber-defense project, ensuring high-quality data ingestion, transformation, and delivery using ETL/ELT tools and big-data tech.
Senior Data Engineer
Senior Data Engineer builds and maintains cloud-based data pipelines and analytics infrastructure to enable data-driven decisions across Bunge’s global operations.
Senior Data Engineer
Build and own the data platform that powers AI model compression and quantum-inspired optimization products, designing ETL pipelines, lakehouse architectures, and governance workflows in Python/SQL on cloud platforms.
Senior Data Engineer
Design and build scalable data platforms and ETL pipelines using Python, SQL, Spark, and cloud tools (AWS/Azure/GCP) to enable clean, governed data for analytics and AI.
Data Engineer - AWS
Design and build scalable cloud data pipelines on AWS, using Python, Spark, and modern data architectures to enable reliable analytics and business insights.
Data Engineer - GCP
Build and maintain scalable GCP data pipelines and cloud-native analytics solutions using Python, BigQuery, and related GCP services.