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Lonza

Global life sciences contract manufacturer

Data Engineer - Process Analytics & Data Intelligence

Data EngineeringConfirmed live in the last 24 hours
Full-timeVisp, SwitzerlandNo salary listed

About the Job

Requirements

  • Proven experience building, operating, and optimizing production-grade data pipelines in manufacturing, industrial, or operational environments.
  • Strong SQL expertise, including the ability to design efficient data models and optimize queries for high-volume operational workloads.
  • Hands-on experience with ETL/ELT pipeline development and integrating 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.

Responsibilities

  • Design, build, and operate automated data pipelines that integrate 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 support 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 with clean schemas, consistent semantics, and 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.

About the Company

Lonza

Global life sciences contract manufacturer

Lonza is a global provider of development and manufacturing services for the pharmaceutical, biotechnology, and nutrition sectors. It supports clients from early development through to commercial production, offering integrated processes such as process development, GMP manufacturing, formulation, fill-finish, and quality assurance to bring medicines and nutrition products to market. Lonza’s model is built on end-to-end CDMO capabilities, enabling companies to move from concept to scalable, compliant production with reliable supply chains. What sets Lonza apart is its long history and global footprint, combining decades of experience across chemistry, biology, and nutrition with a broad, end-to-end service network that supports projects from discovery to commercialization. The company aims to be a trusted, long-term partner in life sciences by helping customers efficiently develop and manufacture their products at scale while maintaining strict regulatory and quality standards.

Company size
10,001+
Company stage
IPO
Headquarters
Basel, Switzerland
Founded
1897

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