Data Engineer – PPI Digital Transformation (Multi-site)

Work Schedule Standard (Mon-Fri) Environmental Conditions Office Job Description Company Introduction As part of the Thermo Fisher Scientific team, you’ll discover meaningful work that makes a positive impact on a global scale. Join our colleagues in bringing our Mission to life every single day to enable our customers to make the world healthier, cleaner, and safer. We provide our global teams with the resources needed to achieve individual career goals while helping to take science a step beyond by developing digital and data-driven solutions that improve manufacturing performance, operational excellence, and decision-making across our sites worldwide. DESCRIPTION Join the PPI (Practical Process Improvement) Digital & Analytics team at Thermo Fisher Scientific as a Data Engineer , where you will contribute to the design and delivery of data solutions supporting manufacturing and operational excellence initiatives across multiple sites. You will be part of a structured Data Engineering sub-team , working alongside other Data Engineers and a Senior Data Engineer, and collaborating closely with Data Science, IIoT, IT, and Digital Project Management teams. The role focuses on building reliable, scalable, and secure data platforms that enable analytics, reporting, and advanced digital use cases. This position operates in a matrix, multi-site environment , requiring strong collaboration skills, openness to shared ways of working, and the ability to balance priorities across different stakeholders and locations. The role offers the opportunity to grow technically while contributing to impactful digital transformation initiatives within a manufacturing context. Key Responsibilities Design, develop, and maintain scalable data pipelines and ETL processes integrating data from multiple sources and systems. Develop and manage data warehouses and data lakes, ensuring data quality, reliability, and performance. Design and optimize databases and data models to support business intelligence and analytics use cases. Implement data quality controls, monitoring, and automated validation procedures. Build and maintain cloud-based data infrastructure using modern data platforms and technologies. Collaborate with data scientists to deploy analytical and machine learning solutions into production environments. Enable secure and efficient data access for site users and digital applications. Support data governance, security, and compliance standards in collaboration with IT and corporate teams. Work closely with Digital Project Managers to support planning, prioritization, and delivery of data initiatives. Contribute to technical discussions, peer reviews, and continuous improvement activities within the Data Engineering sub-team. Site & Collaboration Model The Data Engineer is expected to work effectively within a distributed team , collaborating remotely with colleagues across different manufacturing sites within EU/APAC sites. REQUIREMENTS Minimum Qualifications Bachelor’s degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, or a related field. 3+ years of experience in Data Engineering, Business Intelligence or similar roles. Strong SQL expertise (complex queries, optimization, database design; MSSQL, Oracle). Experience with data warehousing, dimensional modeling, and business intelligence concepts. Experience with ETL tools and frameworks. Experience with data visualization and data modeling tools (Power BI). Experience with cloud platforms ( Azure / Microsoft Fabric ). Proficiency in Python for data processing. Fluency in English and Italian. Preferred Qualifications Master’s degree in a relevant technical field. Industry certifications (cloud or data platforms). Experience with Git-based version control and CI/CD pipelines. Knowledge of data governance frameworks. Familiarity with IIoT data and industrial data integration. Experience in manufacturing, consulting, or enterprise digital environments. Key Competencies & Soft Skills Proactivity to satisfy customer needs. Detail-oriented and analytical mindset. Strong ability to work within structured technical teams , contributing to shared standards and best practices. Collaborative mindset and openness to technical guidance, mentoring, and peer review. Ability to balance individual ownership with team-based delivery. Effective communication skills, with the ability to interact with stakeholders at different seniority levels. Proactive attitude and focus on continuous learning and technological discovery. Interest in digital technologies applied to manufacturing and operational excellence. Additional Information Occasional travel may be required to support collaboration and site activities ( estimated 0–20% ).