Data Engineer - Agentic AI

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: November

Location: Barcelona, 2days on site, 3 days remote

Duration: 6 months contract + extensions

Language: English and Spanish

• AI & 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.

• 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.