We are seeking a proactive Data Engineer to play a pivotal role in transforming our operational capabilities. In this role, you will identify core business processes and design, build, and deploy intelligent, automated workflows powered by state-of-the-art AI agents.
Start Date: NovemberLocation: Barcelona, 2days on site, 3 days remoteDuration: 6 months contract + extensionsLanguage: English and SpanishAI & Automation Integration: Develop and maintain AI agent-driven workflows to automate and optimize operational tasks across the organization.
Process Identification: Design, build, and deploy data pipelines that support the discovery and mapping of business processes.
ETL/ELT Pipeline Orchestration: Build, maintain, and orchestrate robust data pipelines using DBT and Airflow. Data Warehouse Optimization: Work extensively with Snowflake for data modeling, transformation, and performance tuning. Production Engineering: Develop scalable, production-grade code in Python for high-throughput data processing and AI/agent integration. Cloud & Infrastructure: Deploy, manage, and monitor data and AI solutions on AWS cloud infrastructure. Cross-Functional Collaboration: Partner with stakeholders across business units to pinpoint high-impact automation opportunities. Data Governance & Quality:



Ensure data quality, governance, and security best practices across all pipelines and automation workflows. Documentation & Standards: Document technical solutions, architecture designs, and contribute to the continuous improvement of engineering standards.
Required

Skills:
Snowflake: Proven hands-on experience with data modeling, data transformation, and performance optimization. Python: Advanced proficiency in writing clean, scalable, production-grade code. AWS: Hands-on experience deploying, managing, and monitoring solutions within AWS cloud environments. AI Agent Automation: Demonstrated experience designing or implementing AI agent-based automation for business processes. Data Architecture: Strong understanding of end-to-end data pipeline architecture and best practices. Language: Fluent in English (written and spoken). DBT & Airflow: Hands-on expertise with DBT and/or Apache Airflow (Nice to Have). LLM & AI Frameworks: Familiarity with modern LLM/AI agent frameworks. LLM Orchestration: Hands-on experience with frameworks such as LangChain, LangGraph, or Semantic Kernel. MLOps / LLMOps: Background in MLOps/LLMOps deployment, monitoring, and evaluation practices.

📌 Data Engineer (Barcelona)
🏢 Red Global
📍 Barcelona