Manufacturing Process Data Engineer III - Biopharmaceuticals

Role Summary

This position is based in Framingham, MA, and will work directly with process engineers to manage the development and design of automated systems as well as to provide advanced analytics and system modeling support across multiple functions of Cell Culture, Purification and Analytics.

• Design, develop, and maintain robust ETL processes to integrate data from various sources
• Create and optimize data models to support business intelligence and analytics initiatives
• Collaborate with cross-functional teams to identify data requirements and deliver tailored solutions
• Implement data quality checks and ensure data integrity across all systems
• Develop and maintain documentation for data processes, models, and pipelines
• Continuously improve data infrastructure and processes to enhance performance and scalability
• Partner with internal stakeholders from multiple departments to identify opportunities for applying data engineering and process monitoring solutions for new manufacturing facilities
• Exploit opportunities to leverage manufacturing data to develop data engineering and machine learning (ML) models and real-time process monitoring approaches
• Translate data analytics outcomes to non-scientific audiences, champion data-driven decision making and empower end-users to perform simple analytics
• Support various stakeholders to ensure timely delivery of data engineering, visualization, ML and AI capabilities. Promote a strong quality mindset with a focus on data integrity, validation, and data governance

• Required:
  
  Bachelor's degree with 5+ years or a Master's Degree with 3+ years or a PhD with 1 year of experience in data sciences, computer sciences, chemical engineer or a related discipline in pharmaceutical industry
• Required:
  
  Proficiency in SQL and experience with relational databases
• Required:
  
  Experience with ETL tools and processes
• Preferred:
  Experience working in biopharmaceutical manufacturing or other GxP-regulated environments (e.g., GMP, GLP, GCP) with strong understanding of regulatory compliance requirements and data integrity
• Preferred:
  Strong knowledge in working with data historian systems, Manufacturing Execution System (MES) and IoT solutions
• Preferred:
  High level of familiarity using platforms such as Snowflake or Github and no-code/low-code applications such as Dataiku
• Preferred:
  Strong aptitude in developing data visualization platforms (Power BI, R Shiny, Streamlit, etc.)
• Preferred:
  Experience in using SAP data and the use of transactional and genealogy data in data contextualization
• Preferred:
  Experience in writing reports and knowledge management documentation