Freelance Data Project Manager

Client of Novancy One

Status : Freelance.

Main Mission:

Defining, designing and implementing an end-to-end data solution for an industrial environment, including:

1. Framework & Governance :
   • Identify priority use cases (production, predictive maintenance, logistics, etc.).
   • Define the governance model (ownership, quality, security, compliance).
   • Structuring a glossary of business tier (KPIs: tonnage, content, Capex/Opex, etc.).
2. Data Ingestion & Integration :
   • Real-time collection (IoT sensors: OPC UA, PI System, SCADA) and batch data (SAP S/4, Ariba, HR, Finance).
   • Integration of geospatial data (GIS, drones).
   • Deployment of ingestion tools (Kafka, Flink, NiFi, StreamSets).
3. Architecture Data Platform :
   • Implementation of a Data Lakehouse (MinIO, Iceberg, Trino/Starburst).
   • Zoning (Bronze/Silver/Gold) et virtualisation (Denodo/Dremio).
   • Security: RBAC, encryption, data lineage.
4. Quality & Rational Operational Governance :
   • quality controls (e.g. critical data pH, m content rate).
   • Anomaly monitoring and cataloging (OpenMetadata/Ataccama).
5. Analytics & Reporting :
   • Design of dashboards (production, energy, logistics) via Power BI/Tableau.
   • Definition of KPIs (equipment availability, cost per tonne, CO2 emissions).
6. Advanced Analytics & AI :
   • Use case deployment: predictive maintenance (mining equipment), energy optimization, product quality.
   • Safety/environment applications (dike stability, missions).
7. Change Management & Upskilling :
   • Training of technical teams on analytics tools.
   • Implementation of Agile/Lean processes and leveraging the benefits of data.

Required Profile:

• Proven experience in managing complex data projects (industrial, mining or energy environment appreciated).
• Mastery of technologies: Data Lakehouse, real-time ingestion (Kafka, Flink), IoT, SAP, virtualization.
• Skills in data governance, quality and compliance.
• Expertise in analytics (industrial KPIs) and AI/ML (predictive maintenance).
• Capacity to train and support change.