Data Engineer, Back-End Architect

Minor Hotels Europe and Americas

Data Engineer and Back-End Architect designing robust data architectures and collaborating with data science teams for Allianz. Focusing on data extraction, transformation, and model management.

Posted 6/5/2026full-timeMilan • 🇮🇹 ItalyMid-LevelSeniorWebsite

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

SQLETL processesdata modelingPythonJuliaC++DataOpsMLOpsNoSQLcontainerization

Soft Skills

communication skillscollaborationproblem-solvingadaptabilitywillingness to travel

Tools & Technologies

AWSGCPAzureMLFlowDockerKubernetes

Certifications & Qualifications

Master’s Degree in Computer ScienceMaster’s Degree in Computer EngineeringMaster’s Degree in Data Engineering

Industry Keywords

Back-End Architecturesdata engineeringdata pipelinesdata workflowsproduction processes

Tech Stack

Tools & technologies

AWSAzureCloudDockerETLGoogle Cloud PlatformKubernetesNoSQLPythonSQL

About the role

Key responsibilities & impact

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

What you’ll need

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.

Benefits

Comp & perks

Health insurance
Retirement plans
Paid time off
Professional development
International travel opportunities