Engage in collaborative efforts with the data science team to comprehend data requirements and develop robust architectures and data models
Enhance business processes by proficiently managing the lifecycle of data and AI models
Architect, construct, and launch innovative data extraction, transformation, and loading processes to craft data pipelines, utilizing advanced object-oriented programming languages and modern web frameworks
Maintain and improve existing production processes by identifying and implementing optimized, scalable solutions
Contribute to Research and Development initiatives to discover and integrate cutting-edge technical solutions that propel the organization forward
Requirements
Master’s Degree in Computer Science, Computer Engineering, Data Engineering or a closely related field.
5-10 years working experience in Back-End Architectures and Data Engineering
Knowledge in SQL, ETL processes, data modeling, and programming language (e.g. Python, Julia, C++)
Experience with DataOps practices, contributing to the continuous improvement of data workflows
Knowledge of Cloud Services including AWS, GCP, Azure, and their application in data engineering tasks
Familiarity with MLOps concepts and tools like MLFlow to streamline machine learning lifecycle management
Proficient understanding of both SQL and NoSQL database technologies
Experience with containerization and orchestration technologies such as Docker and Kubernetes
Fluency in Italian and English, written and spoken
Excellent communication skills
Willingness to travel internationally for business needs.