Process Data Engineer III - MSAT

Sanofi • Framingham, MA

1d • Hybrid

About The Position

We deliver 4.3 billion healthcare solutions to people every year, thanks to the flawless planning and meticulous eye for detail of our Manufacturing & Supply teams. With your talent and ambition, we can do even more to protect people from infectious diseases and bring hope to patients and their families. Sanofi Global MSAT (Manufacturing Sciences, Analytics, and Technology) acts as a crucial link between our R&D and Manufacturing facilities, playing a vital role in securing the present portfolio and delivering future launches of high-quality and innovative drugs and vaccines. By driving its own transformation, Global MSAT fulfils an important function by providing day-to-day Manufacturing Support, focusing on technical and process aspects, effective Life Cycle Management, process robustness enhancement, and yield improvement to optimize performance. Under the leadership of MSAT and in partnership with many other functions (Manufacturing 4.0, Digital, M&S, R&D), the Process Data Science & Digital transformation (DSD) team is a transversal team driving innovations, developments, expansion, and integration within the MSAT day-to-day operational space. 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. We are an innovative global healthcare company with one purpose: to chase the miracles of science to improve people’s lives. We’re also a company where you can flourish and grow your career, with countless opportunities to explore, make connections with people, and stretch the limits of what you thought was possible. Ready to get started? Hybrid - 3 days per week in Framingham, MA - required.

Requirements

• 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.
• Proficiency in SQL and experience with relational databases (e.g., MySQL, PostgreSQL)
• Strong programming skills in Python or R
• Experience with ETL tools and processes

Nice To Haves

• Strong knowledge in working with data historian systems, including Aspen IP21 or AVEVA PI Asset Framework (AF) & PI Event Frames – infrastructure, Manufacturing Execution System (MES) and IoT solutions.
• High level of familiarity using platforms such as Snowflake, AWS, Azure, Github and no-code/low-code applications such as Dataiku.
• Strong aptitude in developing data visualization platforms (Power BI, R Shiny, Streamlit, etc.)
• Experience in using SAP data and the use of transactional and genealogy data in data contextualization.
• Experience in writing reports and knowledge management documentation.

Responsibilities

• 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.

Benefits

• Bring the miracles of science to life alongside a supportive, future-focused team.
• Discover endless opportunities to grow your talent and drive your career, whether it’s through a promotion or lateral move, at home or internationally.
• Enjoy a thoughtful, well-crafted rewards package that recognizes your contribution and amplifies your impact.
• Take good care of yourself and your family, with a wide range of health and wellbeing benefits including high-quality healthcare, prevention and wellness programs and at least 14 weeks’ gender-neutral parental leave.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees