Data Engineer – Process Analytics & Data Intelligence 80-100%

Relocation assistance is available for eligible candidates and their families, if needed

Within the Process Analytics & Data Intelligence (PADI) team, embedded directly in Operations, we build production-ready data infrastructure that connects process, execution, and development data into a coherent and trusted foundation used daily by MSAT, Process Development, Operations, and global data teams. 

We are looking for a Data Engineer – Process Analytics & Data Intelligence in Visp to design, build, and operate this data foundation and support reliable, scalable use of operational data across teams 

This is a fully site‑based role. Working together in person supports close, real‑time collaboration and the technical precision needed to manufacture medicines to the highest quality and safety standards.

What you’ll get:

• An agile career and dynamic working culture.

• An inclusive and ethical workplace.

• Compensation programs that recognize high performance.

• In addition to a competitive salary, you can expect numerous lifestyle, family, and leisure benefits. Our full list of tailored local benefits in Visp can be found on 9cd58bc563c44174b5a4f5fedd506597

What You Will Do: 

• Design, build, and operate automated data pipelines integrating distributed file-based data stores and raw operational system databases, including historians (PI), MES, ELN and instrument data, into a coherent, end-to-end operational data foundation. 

• Replace manual, file-based data handling with governed, versioned and traceable data flows that stand up to daily operational use. 

• Implement and enforce data quality checks, validation rules and monitoring to ensure data reliability at scale in an operational environment. 

• Deliver analytics-ready datasets (clean schemas, consistent semantics, time-aligned data) to downstream BI, advanced analytics and modeling layers supporting operational decision-making. 

• Work closely with MSAT, Process Development, Automation, QA, IT and global data teams to align data models, definitions and integration patterns across the organization. 

• Continuously improve pipeline performance, robustness and maintainability in line with operational priorities. 

What we are looking for:

• Proven experience building, operating, and optimizing production-grade data pipelines in manufacturing, industrial, or operational environments.

• Strong SQL expertise with the ability to design efficient data models and optimize queries for high-volume operational workloads.

• Hands-on experience with ETL/ELT pipeline development and integration of process, execution, and operational data sources.

• Practical knowledge of OT systems, including MES, PI Historian, instrument data, or similar industrial data platforms.

• Solid understanding of data quality, lineage, traceability, governance, and compliance, ideally within GxP-regulated environments.

• Experience with Azure data services, including Azure Data Factory, Azure Data Lake/Blob Storage, Git-based version control, and cloud-native data architectures.

• Background in biopharma, life sciences, manufacturing, or operations data, with the ability to translate complex operational processes into scalable data solutions.

About Lonza:

At Lonza, our people are our greatest strength. With 30+ sites across five continents, our globally connected teams work together every day to manufacture the medicines of tomorrow. Our core values of Collaboration, Accountability, Excellence, Passion and Integrity reflect who we are and how we work together. Everyone’s ideas, big or small, have the potential to improve millions of lives, and that’s the kind of work we want you to be part of.

Innovation thrives when people from all backgrounds bring their unique perspectives to the table. At Lonza, we value diversity and are committed to creating an inclusive environment for all employees. If you’re ready to help turn our customers’ breakthrough ideas into viable therapies, we look forward to welcoming you on board.

Ready to shape the future of life sciences? Apply now.