AI Data Engineer: Data Platform & ETL Specialist

Sofidel S.p.A. is seeking a data engineer to join the Corporate Data Platform team in Porcari. You will design and implement data integration pipelines, build scalable data models, and ensure data quality across the enterprise. This role offers exposure to cutting-edge data architectures and collaboration with IT, business, and analytics teams.

You will work with SQL, Python, Spark, and cloud data services, helping to deliver reliable data solutions for reporting and AI initiatives worldwide.

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. 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. International work environment Professional growth Language learning program Full-time employment