Data Engineer
Pubblicato il 10-09-2026 - Moncler in Turbigo
Overview
We are looking for an engaged and detail-oriented Data Engineer to join the Data Platform & AI Team at our HQ in Milan.
Your Impact
The Data Engineer will build and optimize scalable data pipelines and models, delivering reliable, analytics-ready data and enabling data-driven decision-making across the organization.
Responsibilities
- Design, develop, and maintain scalable batch and streaming data pipelines for data ingestion, transformation, and delivery.
- Collaborate with BI teams to provide high-performing data models, data marts, and semantic layers that support business needs.
- Implement data quality, monitoring, and observability frameworks to ensure data reliability and proactively identify issues.
- Manage data incidents through root cause analysis, resolution, and continuous improvement to prevent recurrence.
- Translate business and analytical requirements into scalable, maintainable, and efficient data solutions.
Qualifications
- Minimum 5 years of professional experience in data engineering or a closely related role.
- Strong SQL skills.
- Experience building transformation layers from raw or semi-structured data into clean, analytics-ready datasets.
- Experience with dbt or similar analytics engineering and transformation tools.
- Strong understanding of query and workload optimization, including performance tuning (partitioning, pruning, query optimization) and cost efficiency, with a FinOps-oriented mindset for cloud resource usage.
- Hands‑on experience with at least one major cloud provider (GCP, Azure, or AWS).
Preferred Attributes
- Able to communicate clearly with both technical and non-technical people
- Curious and proactive, with a strong problem‑solving mindset
Compensation & Benefits
- Application of CCNL Tessile
- Compensation package range: from 45.000 € to 50.000 € gross
- Competitive Corporate Welfare Services
Moncler Group is an equal opportunity employer, which means we do not discriminate on the basis of ethnic orig