At Bayer, we are visionaries, determined to overcome the greatest challenges facing our planet and contribute to a world where sufficient food and adequate medical care for all people are no longer unattainable goals. We do this with energy, curiosity, and sheer dedication, constantly learning from the people around us, broadening our horizons, improving our skills, and redefining the "impossible." There are many reasons to join us: If you are looking for a diverse and meaningful career where you can truly make a difference alongside other brilliant minds, we want you on our team.

Data Engineer (all genders)

As a Data Engineer (all genders), you will design, implement, and operate data pipelines for our manufacturing data landscape. Your systems will retrieve data from various applications and sources, such as MES, SAP, device databases, historian systems, apps, and production facilities, and provide quality-assured, contextualized data for downstream systems, data science applications, and AI use cases. You will take an active role as an AI Ambassador to promote the use of AI in production-related processes, create AI-ready data pipelines, and ensure compliance with pharmaceutical production, GMP, data, validation, and governance requirements.

YOUR TASKS AND RESPONSIBILITIES

• Responsible for the design, development, operation and maintenance of robust data pipelines for our manufacturing systems data integration systems.
• Support of our datastore/data lake and data warehouse system for collecting, harmonizing and providing manufacturing data using AWS services, as well as handling Databricks as a data lake for data science and AI use cases.
• Responsible for the development of program code as well as for technology and system decisions for the provision and operation of large ETL/ELT processes.
• Working with GitHub as well as established DevOps, versioning and documentation practices
• Interface design and data transformation using integration environments such as Node-RED or comparable technologies, as well as the design and implementation of equipment connectivity and interfaces, e.g., using OPC UA, and the associated data pipelines for the integration of manufacturing assets.
• Active exchange with data scientists to develop and implement predictive models, advanced analytics topics, and AI use cases.
• Taking on the role of AI Ambassador to promote the responsible, user-oriented and regulatory-compliant use of AI in pharmaceutical production, for example by leading and participating in initiatives to integrate AI into production-related processes, including data provision, automation, decision support and continuous improvement.
• Close collaboration within the company with the various specialist departments, central platform functions, the global data scientist community, as well as outside the company with suppliers, technology providers, universities, external consultants and industry partners.

WHAT SETS THEM APART

• Completed university degree in computer science, data engineering, engineering, mathematics, statistics or a comparable field with practical experience in data engineering, data analysis or software development.
• Several years of experience in building scalable data models, data architectures and ETL/ELT pipelines for structured and unstructured data from various sources
• Practical experience working with structured and unstructured data from various sources, as well as experience in developing scripts and tools for faster data processing.
• Proficient use of SQL, cloud platforms (AWS), (un)structured data, and extensive programming experience.
• Knowledge of decentralized systems and agile software development
• Strong ability to collaborate with multiple teams and stakeholders in visible, cross-functional roles, as well as enjoyment in the structured planning and implementation of data and AI initiatives.
• The job holder enjoys defining and managing project plans and the availability of data.
• Fluent German and English skills, both spoken and written.
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