Data Engineer – Process Analytics & Data Intelligence

Posted Yesterday
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Visp, Valais, CHE
In-Office
Mid level
Pharmaceutical
At Lonza, we enable A Healthier World by supporting our healthcare customers on the path to commercialization.
The Role
Design, build, and operate automated, production-ready data pipelines integrating historians, MES, ELN and instrument data into governed, analytics-ready datasets. Implement data quality, lineage, validation and monitoring, deliver time-aligned schemas for BI and advanced analytics, and collaborate with MSAT, Process Development, Automation, QA, IT and global data teams to align models and ensure reliability in regulated manufacturing environments.
Summary Generated by Built In

 

Today, Lonza is a global leader in life sciences operating across five continents. While we work in science, there’s no magic formula to how we do it. Our greatest scientific solution is dedicated people working together, devising ideas that help businesses to help people. In exchange, we let our people own their careers. Their ideas, big and small, genuinely improve the world. And that’s the kind of work we want to be part of.

The actual location of this job is in Visp, Switzerland. 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 to design, build, and operate this data foundation and support reliable, scalable use of operational data across teams 

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. 

 Who You Are: 

  • You think in pipelines, schemas and failure modes, not files and manual workarounds. 

  • You design repeatability, observability and scale in environments where reliability matters. 

  • You are comfortable working across OT systems, MES, and cloud data platforms. 

  • You take end-to-end ownership, from source systems to analytics consumers. 

  • You simplify complex operational data landscapes without losing critical process detail. 

What You Bring: 

  • Hands-on experience building and operating production data pipelines in operational or industrial environments. 

  • Strong SQL expertise and experience optimizing queries for operational workloads. 

  • Proven experience with ETL / ELT pipelines handling process and execution data. 

  • Hands-on exposure to historians (PI), MES, instrument data, or similar OT systems. 

  • Solid understanding of data quality, lineage, traceability, and governance ideally in regulated (GxP) environments. 

  • Experience with cloud data platforms, preferably Azure, including building and managing data pipelines (Azure Data Factory), data storage solutions (Azure Data Lake/Blob Storage), and version control using Git. 

  • Background in biopharma, manufacturing, or operations data is strongly preferred. 

  • Education: Degree in Engineering, Data Science, Computer Science, or a related technical field preferred — equivalent operational experience will be considered. 

Every day, Lonza’s products and services have a positive impact on millions of people. For us, this is not only a great privilege, but also a great responsibility. How we achieve our business results is just as important as the achievements themselves. At Lonza, we respect and protect our people and our environment. Any success we achieve is no success at all if not achieved ethically.

People come to Lonza for the challenge and creativity of solving complex problems and developing new ideas in life sciences. In return, we offer the satisfaction that comes with improving lives all around the world. The satisfaction that comes with making a significant difference.

Lonza is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, religion, color, national origin, sex, sexual orientation, gender identity, age, status as a qualified individual with disability, protected veteran status, or any other characteristic protected by law.

Skills Required

  • Hands-on experience building and operating production data pipelines in operational or industrial environments.
  • Strong SQL expertise and experience optimizing queries for operational workloads.
  • Proven experience with ETL / ELT pipelines handling process and execution data.
  • Hands-on exposure to historians (PI), MES, instrument data, or similar OT systems.
  • Solid understanding of data quality, lineage, traceability, and governance (ideally in regulated GxP environments).
  • Experience with cloud data platforms and building/managing data pipelines and storage (preferably Azure; e.g., Azure Data Factory, Azure Data Lake/Blob Storage).
  • Experience using version control (Git).
  • Background in biopharma, manufacturing, or operations data.
  • Degree in Engineering, Data Science, Computer Science, or related technical field; or equivalent operational experience.
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The Company
HQ: Basel
0 Employees
Year Founded: 1897

What We Do

At Lonza, we enable A Healthier World by supporting our healthcare customers on the path to commercialization. Our community of 16,000 talented employees work across a global network of more than 30 sites to deliver for our customers across the pharma, biotech and nutrition markets.

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