DATA ENGINEER

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