Stage Data Visualization
Pubblicato il 17-08-2026 - Aretè & Cocchi Technology in Romano di Lombardia
As Data Visualization & Analytics Specialist you will be part of the Energy Carriers Business Line within COSEN (Energy Carriers Construction & Subcontracts Services).
Se desidera saperne di più su questa possibilità o sta pensando di candidarsi, la preghiamo di leggere le seguenti informazioni.The role involves conducting thorough analyses of construction quantities and costs to deliver accurate forecasts for project completion. It ensures transparency in payment records, facilitates claims evaluation, establishes pricing benchmarks, and supports informed decisions regarding subcontracting strategies through data‐driven methodologies.
Responsibilities
- We are seeking a Data Visualisation & Analytics Specialist with proven experience in using Microsoft Power BI. The selected candidate will be responsible for designing and implementing Business Intelligence solutions, overseeing the entire process from data collection and modelling to the creation of effective dashboards and reports.
- Design, develop, and maintain data pipelines to ingest, transform, structure,
and deliver datasets from multiple internal and external sources.
- Enhance data quality, reliability, and governance, ensuring compliance with corporate standards, metadata requirements, and lifecycle management rules.
- Collaborate closely with analysts and engineering stakeholders to understand data needs, translate requirements into technical solutions, and support advanced analytics and reporting activities.
- Implement data cleaning, validation, and enrichment processes to deliver consistent, high‐quality datasets for construction management.
- Contribute to documentation, standards, and best practices, promoting continuous improvement in data engineering methodologies.
EducationMaster's or bachelor's degree in computer science or related field.
Technical Knowledge
- Ability to design interactive dashboards and visual reports in Power BI.
- Solid experience in data wrangling, transformation, aggregati