AI Data Engineer
At a glance
Mid-level Data Engineering role at Sofidel. Porcari.
Pay not stated Data Engineering salary
dataroles summary, based on the employer's posting.
What you'll do
- Build and maintain ETL/ELT pipelines that move data from business and manufacturing systems into usable form
- Connect databases, ERP and factory systems, files, APIs, and other applications
- Create data models for reporting, analytics, and AI, while maintaining data quality across the platform
- Monitor data workflows, resolve failures and inconsistencies, and improve performance
- Support the Data Platform and its Agent Platform services, working with business, IT, vendor, and data specialists
What you bring
- A relevant master's degree in computer science, engineering, data science, or another STEM field
- Three to five years in a comparable role, with hands-on ETL/ELT pipeline design and data integration
- Strong SQL and Python skills, plus experience with relational and NoSQL databases
- Knowledge of data modeling, modern warehouse, lake, or lakehouse architectures, and data engineering tools
- Very good English and working knowledge of Italian
Who this fits
This role suits a mid-level data engineer who can work independently on reliable data pipelines and collaborate across technical and business teams. The position is based in Porcari and is full-time.
From the employer
The Sofidel Group
Sofidel, headquartered in Porcari (Lucca), is a global leader in tissue paper production. With operations in 12 European countries and 12 U.S. States, we employ over 9,500 people dedicated to innovation, sustainability, and inclusivity. Our products—such as toilet paper, paper towels, and napkins—are distributed in more than 50 countries.
We own well-known brands including Regina, Nicky, Sopalin, Le Trèfle, Hakle, Softis, Nalys, Cosynel, and KittenSoft, and also produce for private-label retailers. Through the Papernet brand, we serve the Away-from-Home sector, providing quality solutions for businesses and public spaces.
Wherever you are, Sofidel is there, bringing comfort, quality, and sustainability to everyday life!
PURPOSE
To contribute to the development and enhancement of the Corporate Data Platform and data components developing and maintaining the company's data integration and management solutions and ensuring that data from business and manufacturing systems is collected, transformed, and made available in a reliable, secure, and efficient way.
MAIN RESPONSIBILITIES
- Design, develop, and maintain data integration pipelines (ETL/ELT) to collect and process data from business and manufacturing systems.
- Integrate data from multiple sources, including databases, ERP systems, factory systems, files, APIs, and other applications.
- Develop and maintain data models and structures supporting reporting, analytics, and AI solutions.
- Ensure data quality, accuracy, consistency, reliability, and availability across the corporate data ecosystem.
- Monitor data workflows and proactively resolve performance issues, failures, and data inconsistencies.
- Support the development, optimization, and maintenance of the Company's Data Platform and data services supporting the Agent Platform.
- Collaborate with business stakeholders, IT teams, vendors, and Data/AI specialists to deliver effective data solutions.
- Implement and follow data governance, security, and best practice standards.
- Prepare and maintain technical documentation, development standards, and operational procedures.
- Contribute to the continuous improvement, scalability, and long-term evolution of the company's data architecture and platforms.
Your skills for the application:
- Master's degree in Computer Science, Computer Engineering, Data Science, or related STEM disciplines.
- 3–5 years of experience in similar roles.
- Excellent knowledge of relational and NoSQL databases.
- Proficiency in SQL and Python.
- Experience designing ETL/ELT pipelines and data integration processes.
- Knowledge of data modeling and modern data architectures, including Data Warehouses, Data Lakes, and Lakehouses.
- Experience with data engineering tools and frameworks such as Spark, Databricks, Delta Lake, Parquet, Airflow, or equivalent technologies.
- Familiarity with cloud environments such as Azure, AWS, or GCP and their related data services.
- Knowledge of code versioning tools such as Git and, preferably, CI/CD practices.
- Experience in monitoring data processes, data quality, logging, and troubleshooting.
- Knowledge of data governance principles, data security, and access management.
- Very good written and spoken English; good working knowledge of Italian.
These technical skills are considered as a plus:
- Experience with streaming data, such as Kafka or similar technologies.
- Knowledge of dbt, Docker, Kubernetes, or Terraform.
- Experience in industrial/manufacturing environments and data integration from factory systems.
- Familiarity with platforms or architectures supporting AI/ML or agentic use cases.
- Certifications in Cloud, Data Engineering, or Big Data.
Your Soft Skills:
- Strong analytical thinking and problem-solving attitude.
- Ability to explain complex technical concepts in a clear and accessible way to non-specialists.
- Collaborative, with a team-oriented and cross-functional approach in multidisciplinary environments.
- Proactive attitude and operational autonomy, curious and open to explore new technologies and cross-sector solutions.
- Attention to quality, documentation, and continuous improvement; high standards of integrity, confidentiality and professional ethics.
WHAT WE OFFER
- A full-time employment
- The chance to work in an international Group and a concrete opportunity for professional growth
- A dynamic environment based on teamwork
- Sofidel Language Learning Programme through innovative digital platform
OUR APPROACH TO COMPENSATION
We are committed to offering a fair and transparent compensation approach.
This role sits within a salary range of €33.000 – €40.000, defined based on internal equity and external market benchmarks. The final offer will be tailored, reflecting the selected candidate’s experience, skills, and overall contribution to the role.