Experteer Overview
Se anima a todos los posibles solicitantes a que se desplacen y lean la descripción completa del puesto antes de presentar su candidatura.
In this Senior Analyst role you own the analytical backbone for EU Inbound Supply Chain, designing scalable data architectures and production-grade analytics systems. You will work across real-time streaming and batch processing to deliver timely data for strategic decisions. The position blends data engineering with cross-functional influence, enabling GenAI-enabled analytics to scale insights. You’ll present to senior leadership and help transform ambiguous problems into measurable outcomes.
Compensaciones / Incentivos
• Design end-to-end data architectures for real-time (Kinesis, Flink) and batch (EMR, Redshift, Athena) workloads
• Build production-grade ETL/ELT pipelines processing multi-TB datasets with data-quality checks and monitoring
• Architect real-time analytics for operational monitoring of inbound flows, delivery accuracy, dock congestion, and disruptions
• Own metric frameworks and reporting, design KPIs,
and automate dashboards (QuickSight) with root-cause context
• Develop GenAI-driven tooling and agentic workflows to automate narratives and root-cause analysis
• Conduct deep-dive investigations across multi-source datasets to quantify network-wide impact using statistical methods
Responsabilidades
• Bachelor's degree in a quantitative field
• Experience in analytics, data engineering, or BI at a large-scale enterprise with data-warehouse xqbhyrx architecture, data modeling, and ETL/ELT design
• Advanced SQL and Python for handling multi-TB datasets and pipeline automation
• Experience with real-time streaming and batch systems (Kinesis, Kafka, Flink; EMR, Hive) and data-visualization tools (QuickSight, Tableau)
• Experience translating operational problems into analytical solutions and communicating results to senior leadership (Director/VP) with quantified impact
Requisitos principales
•
📌 Sr. Analyst , Global Operational Excellence (Madrid)
🏢 Amazon
📍 Madrid