Senior Engineer I, Manufacturing Sciences  – Data Analytics

About This Role    The Senior Engineer I, Manufacturing Sciences - Data Analytics, will play a critical role in enabling data-driven decision making across manufacturing operations and technical functions. This position is responsible for developing and deploying manufacturing data solutions that improve process understanding, operational performance, investigations, and reporting capabilities. Working closely with Automation, IT, and other cross-functional partners, you will design and maintain data models for access, contextualization, and analytics tools that connect diverse manufacturing systems and support emerging AI-driven applications.  Working with Manufacturing Sciences and Technical Development, you will leverage analytics tools to provide process insight, support investigations and work toward process improvement. This is a hybrid position requiring onsite collaboration for three days per week, at minimum. What You’ll Do    Define manufacturing data requirements and establish processes that ensure data quality, reliability, and meaningful business insights. Partner with Manufacturing Sciences, Technical Development, and other stakeholders to understand business needs and translate them into analytical and data solutions. Build and maintain product-specific data configurations, mappings, documentation, and ETL processes across multiple source systems. Develop and support integrations with enterprise manufacturing platforms including DeltaV, Syncade, PI, LabWare LIMS, Oracle EBS, Snowflake, and Statistica. Enable and support AI-based capabilities, including semantic search, document comparison, and automated report generation. Create clear technical documentation and communicate methodologies, findings, and recommendations to cross-functional teams. Support manufacturing investigations, process improvement initiatives, and GMP reporting activities through effective data management, analysis, and modeling. Collaborate across technical and operational organizations to advance digital manufacturing and data modernization efforts.

You are a data-driven engineer who enjoys solving complex manufacturing and technical challenges through analytics and technology. You thrive in cross-functional environments, translating operational needs into scalable data solutions while balancing technical excellence with practical business impact.

Bachelor’s degree in relevant scientific or technical fields from an accredited college or university. At minimum 4 years of directly relevant data analytics experience. Master’s degree may be considered as relevant experience. Experience working with manufacturing, process, engineering, and/or operational data. Strong understanding of data management, data quality, and analytics principles. Experience building and maintaining data pipelines, integrations, or ETL workflows. Demonstrated ability to work with multiple enterprise data sources and manufacturing systems. Experience with creating technical documentation and presenting findings to diverse audiences.

Experience within biotechnology, pharmaceutical, life sciences, GMP, or regulated manufacturing environments. Knowledge of manufacturing systems including DeltaV, Syncade, PI, LabWare LIMS, Oracle EBS, Snowflake, or Statistica. Experience supporting data platforms, reporting solutions, and advanced analytics initiatives. Knowledge of analytics platforms including Spotfire, PowerBI, Tableau Experience in predictive process modelling and use of data, modeling, and machine learning to gain process insights Knowledge of statistical programming languages, such as R or Python Familiarity with AI, machine learning, semantic search technologies, or generative AI applications. Experience partnering with manufacturing sciences, process engineering, automation, or technical development teams. Understanding of data contextualization and digital transformation initiatives within