Cloud Data Engineer - Milan (Hybrid) - 12 months

Global Enterprise Partners; Lombardia; Hybride; EUR 75 000 - 110 000; Plein temps

Résumé du poste

Global Enterprise Partners is seeking an experienced Cloud Data Platform Engineer to join a large-scale enterprise transformation. The role focuses on designing, developing, and maintaining cloud-native data solutions that power business intelligence, analytics, and AI-driven initiatives.

You will design scalable data platforms in AWS, build robust data pipelines with Python, manage Kubernetes workloads, and implement Airflow-driven workflows with Grafana-based monitoring.

Qualifications

• Proven experience delivering enterprise-scale data engineering solutions.

Responsabilités

• Design and implement scalable data platforms within AWS cloud environments.
• Develop and optimise data pipelines using Python and modern data engineering practices.
• Manage and support containerised workloads running on Kubernetes.
• Build, schedule, and monitor workflows using Apache Airflow.
• Implement monitoring, alerting, and observability solutions using Grafana and related tooling.
• Collaborate with data scientists, platform engineers, and business stakeholders to support AI and advanced analytics use cases.
• Ensure platform reliability, performance, scalability, and data quality.
• Contribute to automation, DevOps, and cloud engineering best practices.

Connaissances

AWS cloud

Kubernetes

Python

Airflow

Grafana

Data engineering

AI/ML ecosystems

Cloud native

Stakeholder mgmt

Outils

Airflow

Kubernetes

Grafana

AWS

Description du poste

Location: Milan, Italy (Hybrid)

Contract Duration: 12 Months

Start Date: 30 November

An exciting opportunity has arisen for an experienced Cloud Data Platform Engineer to join a large-scale enterprise transformation programme. The successful consultant will be responsible for designing, developing, and maintaining cloud-native data solutions that support business intelligence, analytics, and AI-driven initiatives.

Key Responsibilities

• Design and implement scalable data platforms within AWS cloud environments.
• Develop and optimise data pipelines using Python and modern data engineering practices.
• Manage and support containerised workloads running on Kubernetes.
• Build, schedule, and monitor workflows using Apache Airflow.
• Implement monitoring, alerting, and observability solutions using Grafana and related tooling.
• Collaborate with data scientists, platform engineers, and business stakeholders to support AI and advanced analytics use cases.
• Ensure platform reliability, performance, scalability, and data quality.
• Contribute to automation, DevOps, and cloud engineering best practices.

Required Experience

• Proven experience delivering enterprise-scale data engineering solutions.
• Strong hands‑on expertise with AWS services and cloud infrastructure.
• Experience deploying and managing applications within Kubernetes environments.
• Advanced Python programming skills.
• Experience with Apache Airflow for workflow orchestration.
• Knowledge of Grafana and platform monitoring best practices.
• Familiarity with AI and machine learning ecosystems.
• Understanding of cloud‑native architecture principles.
• Strong stakeholder management and communication skills.

Preferred Experience

• Exposure to Infrastructure as Code practices.
• Experience working within Agile delivery environments.
• Knowledge of CI/CD pipelines and DevOps methodologies.
• Experience supporting analytics or AI‑focused data platforms.

Candidate Profile

• Analytical and solution‑oriented mindset.
• Able to work independently and within international project teams.
• Strong troubleshooting and problem‑solving capabilities.
• Comfortable operating in fast‑paced, enterprise‑scale environments.