Sievo processes procurement data at global scale—equivalent to over 2% of global GDP annually—using a Microsoft-centric stack (Azure, SQL Server, Databricks, MLflow) paired with deep ERP integrations (SAP, Oracle, JD Edwards, Dynamics). The hiring composition reveals data engineering as the primary scaling lever (7 of 12 open roles), with active projects focused on supplier normalization, taxonomy alignment, and anomaly detection in spend data—indicating a shift from static dashboards toward ML-driven spend insights and supplier intelligence.
Tech Stack 19 technologies
Core StackSAP Dynamics 365 Azure Data Factory Databricks Python SQL Server MLflow .NET React C# Oracle EBS JD Edwards Dynamics NAV Data Lake SQL REST API Azure SQL Server Integration Services Microsoft Office
What Sievo Is Building
◆Challenges
- Complex erp integration challenges
- Complex erp landscapes
- Integration challenges during implementation
- Sustainable erp integrations
- Migrating customer supplier data
- Expanding supplier information
- Supplier classification challenges
- Anomaly detection in spend data
- Managing procurement data
- Optimizing costs
▲Active Projects
- Etl architectural design
- Sustainable erp integrations
- Data model feature development
- Building new data model features
- Central supplier database
- Ai-assisted supplier normalization
- Supplier taxonomy alignment
Hiring Activity
10 roles · 6 in 30d
Department
Seniority
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