Data Engineer

Design, develop, and maintain scalable batch and real-time data pipelines on the Databricks platform using PySpark, SQL, and Delta Lake. Build and optimize enterprise data architectures, including medallion frameworks (Bronze, Silver, Gold), ensuring data quality, consistency, and reliability across all layers. Integrate manufacturing and business-critical data sources such as SAP, MES, LIMS, eQMS, and process historians into a unified data ecosystem. Develop and manage automated data workflows, orchestration processes, and reusable data products to support analytics, reporting, and operational excellence. Implement data governance, security, lineage, and compliance standards, ensuring adherence to GMP, GxP, ALCOA+, and data integrity requirements. Monitor and enhance data platform performance through workload optimization, cost management, and adoption of engineering best practices, testing frameworks, and CI/CD processes. Collaborate closely with data scientists, process engineers, business stakeholders, QA, and validation teams to translate business needs into production-ready data solutions. Enable advanced analytics and machine learning initiatives by providing curated datasets, semantic data models, feature engineering capabilities, and self-service analytics foundations.

Bachem is a leading, innovation-driven company specializing in the development and manufacture of peptides and oligonucleotides. With over 50 years of experience and expertise Bachem provides products for research, clinical development and commercial application to pharmaceutical and biotechnology companies worldwide and offers a comprehensive range of services. Bachem operates internationally with headquarters in Switzerland and locations in Europe, the US and Asia. The company is listed on the SIX Swiss Exchange. The Bachem Group is investing in a new site in Sisslerfeld in Northwestern Switzerland. This step is part of our long-term strategy to expand production capacity. The new production site will play a central role in achieving these goals.

• Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Technology, or a related field.

• 5+ years of hands-on experience designing, building, and operating enterprise-scale data pipelines and data platforms.

• Strong expertise in Databricks technologies, including PySpark, Delta Lake, Unity Catalog, and workflow orchestration.

• Proficient in SQL and Python, with a solid understanding of software engineering best practices, testing, and CI/CD methodologies.

• Experience with cloud-based data platforms (AWS and/or Azure) and a good understanding of storage, compute, networking, and identity management.

• Proven track record working in regulated environments, with knowledge of GMP, GxP, data integrity, and audit requirements.

• Experience integrating enterprise and manufacturing systems, ideally including SAP, MES, LIMS, and other OT/IT data sources.

• Pharmaceutical or life sciences industry experience is highly desirable, as is familiarity with modern lakehouse architectures, streaming technologies, data platform validation, and Databricks certifications.