DATA ENGINEER
Pubblicato il 29-10-2026 - Allianz in Pavia
Overview
In this role you will design and implement robust data architectures and pipelines to support data-driven decision making. You will collaborate with data science teams to align data requirements with scalable, production-ready solutions. You’ll drive the ML lifecycle and data ops to accelerate AI initiatives and R&D; efforts. This position sits within the Chief Protection Officer Team, offering impact through cross-functional collaboration and international exposure. You will be empowered to shape data systems that underpin strategic protection-focused initiatives.
Responsabilità
- Collaborate with the data science team to understand data needs and design robust architectures and data models
- Manage the lifecycle of data and AI models to improve business processes
- Architect, build, and deploy data extraction, transformation, and loading processes to create data pipelines using modern web frameworks and object-oriented languages
- Maintain and enhance production data processes by delivering scalable, optimized solutions
- Contribute to R&D; efforts to identify and integrate cutting-edge technical solutions
Requisiti fondamentali
- Master's Degree in Computer Science, Computer Engineering, Data Engineering or related field
- 5–10 years of experience in Back-End Architectures and Data Engineering
- Proficiency in SQL, ETL, data modeling, and programming languages such as Python, Julia, C++
- Experience with DataOps practices and improving data workflows
- Knowledge of cloud services (AWS, GCP, Azure) and their data engineering applications
- Familiarity with MLOps and tools like MLFlow for ML lifecycle management
- Proficiency in SQL and NoSQL databases
- Experience with Docker and Kubernetes for containerization/orchestration
- Fluency in Italian and English (written and spoken)
- Excellent communication skills
- Willingness to travel internationally
- International exposure through academics or professional experience
- Ability to work effectively in a multidisciplinary team
- excellent communication
- team collaboration
- adaptability
- SQL
- ETL
- data modeling