Supply chain platform with real-time data and ML-driven decision intelligence
Cargoo operates a supply chain collaboration platform built on Azure, Python, and Kafka with an active data infrastructure stack (Dagster, Airflow, dbt, Synapse). The hiring profile reveals a data-heavy org: 5 open data roles against just 1 engineering slot signals they're scaling analytics and ML capacity faster than core product, supporting projects around ETL pipelines, advanced analytics, and real-time decision-making. Active work on AI product features and a rates management tool indicates a push toward automated decision support in procurement and planning.
Cargoo is a Swiss-based supply chain collaboration platform for transportation procurement, planning, and execution. The product integrates transportation partners, carriers, and logistics teams into a single workspace, offering real-time data synchronization and visibility across the value chain. Built with cloud-first infrastructure on Azure and a modern data stack (Python, Kafka, dbt, Synapse), the platform centralizes traditionally fragmented logistics operations—replacing email, spreadsheets, and disconnected carrier systems. Customers are mid-market and enterprise logistics operators and freight forwarders managing ocean freight, domestic trucking, and multimodal networks.
Python, SQL, Azure (Synapse, SQL Database), Kafka, Dagster, Airflow, dbt for data; Vue, TypeScript, Tailwind CSS for frontend; Docker, Kubernetes, GitHub Actions for deployment; Jira for project management.
Building data and analytics infrastructure (ETL/ELT pipelines, real-time platforms, ML), designing AI product features, developing a rates management tool, and scaling customer onboarding for a cloud-based supply chain management platform.
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