Big Data Engineer Milano

Big Data Engineer
Milano
Lombardia, Milano

The mission of the Advanced Analytics Solution team is to develop and operate end-to-end automation, analytics, and AI assets to enhance company processes and business outcomes.

As a Big Data Engineer, the role involves close collaboration with analytics, IT, and architecture teams to develop, industrialize, and maintain data pipelines, analytics/AI models, and automation software for production.

Responsibilities also include liaising with the IT department to manage the cloud-based analytics environments utilized by the team.

The role encompasses technology scouting and defining solutions and standards for Data & Analytics across the organization, participating in cross-functional working groups at both local and international levels.

This position offers a dynamic and innovative work environment with opportunities for professional growth and development.

Key Responsibilities: Data Pipeline Development: Design, optimize, and re-engineer data pipelines and analytics models to ensure robust and efficient data processing.

Project Delivery: Deliver automation and analytics artifacts in alignment with project timelines and objectives.

Cross-functional Collaboration: Participate in cross-functional working groups to represent the Advanced Analytics team and contribute to the definition of target solutions.

Cloud Infrastructure Management: Assist team members in managing cloud-based analytics infrastructure in coordination with the IT department.

Operational Monitoring: Develop and implement activities required to operate and monitor production projects effectively.

Technology Scouting: Support the identification and evaluation of new technologies, techniques, and software within the Data & Analytics domain.

Key Requirements/Skills/Experience: Experience: 2+ years of experience in engineering, with a focus on developing and operating analytics/AI assets in large-data contexts.

Education: Master's degree in Computer Science or Computer Engineering.

A PhD or post-graduate courses in related fields (e. g. , HPC, BDE, DS) is a plus.

Technical Proficiency: Excellent knowledge of Python, PySpark, SQL, and scripting.

Proficiency with orchestration tools such as Airflow.

Strong software engineering skills.

Database Knowledge: Good understanding of relational and non-relational databases, ETL processes, CDC, and data streaming tools and techniques.

Cloud Ecosystems: Experience with Microsoft Azure or AWS ecosystems.

Big Data Architectures: Familiarity with analytics and Big Data architectures (e. g. , Kafka, Hadoop, Databricks) and web/cloud technologies (e. g. , Docker, Kubernetes).

Language Skills: Fluent in English, both written and spoken.

Soft Skills: Team spirit, self-motivation, and a proactive, result-driven work style.

Strong ability to meet deadlines, with excellent self-organization.

Strong analytical, problem-solving, and communication skills.

Additional Knowledge: Familiarity with statistics and data science topics, MLOps techniques, network communication protocols, and project management will be considered a plus.

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