Data Engineer: Build Scalable Pipelines & Analytics

Moncler

Turbigo

In loco

EUR 45.000 - 50.000

Tempo pieno

14 giorni+

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Vantaggi offerti da questo lavoro

Competitive Corporate Welfare Services

Descrizione del lavoro

Moncler is seeking a detail-oriented Data Engineer to join the Data Platform & AI Team at our Milan HQ. The role involves building and optimizing scalable data pipelines and models, facilitating data-driven decision-making across the organization.

Candidates require a minimum of 5 years in data engineering, strong SQL skills, and hands-on experience with major cloud providers. The compensation package ranges from 45,000 € to 50,000 € gross annually along with competitive corporate welfare services.

Competenze

  • 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 tools.
  • Hands-on experience with at least one major cloud provider (GCP, Azure, AWS).

Mansioni

  • Design, develop, and maintain scalable data pipelines for data ingestion and transformation.
  • Collaborate with BI teams to provide high-performing data models and data marts.
  • Implement data quality and monitoring frameworks to ensure data reliability.
  • Manage data incidents through root cause analysis and resolution.

Conoscenze

SQL
Data engineering
Data transformation
Cloud services (GCP, Azure, AWS)
Performance tuning

Descrizione del lavoro

Moncler is seeking a detail-oriented Data Engineer to join the Data Platform & AI Team at our Milan HQ. The role involves building and optimizing scalable data pipelines and models, facilitating data-driven decision-making across the organization.

Candidates require a minimum of 5 years in data engineering, strong SQL skills, and hands-on experience with major cloud providers. The compensation package ranges from 45,000 € to 50,000 € gross annually along with competitive corporate welfare services.

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