Senior Engineer I, Manufacturing Sciences – Data Analytics

This is a hybrid position requiring onsite collaboration for three days per week, at minimum.

Responsibilities

• 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.

Requirements

• 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.

Skills

Preferred Skills

• 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 manufacturing operations.

Pay

The base compensation range for this role is $98,000.00 - $127,000.00. Base salary offered is determined through an analytical approach utilizing a combination of factors including, but not limited to, relevant skills & experience, job location, and internal equity. Regular employees are eligible to receive both short-term and long-term incentives, including cash bonus and equity incentive opportunities, designed to reward recent achievements and recognize future potential based on individual, business unit, and company performance.

Benefits

• Medical, Dental, Vision, & Life insurances
• Fitness & Wellness programs including a fitness reimbursement
• Short- and Long-Term Disability insurance
• A minimum of 15 days of paid vacation and an additional end-of-year shutdown time off (Dec 26-Dec 31)
• Up to 12 company paid holidays + 3 paid days off for Personal Significance
• 80 hours of sick time per calendar year
• Paid Maternity and Parental Leave benefit
• 401(k) program participation with company matched contributions
• Employee stock purchase plan
• Tuition reimbursement of up to $10,000 per calendar year
• Employee Resource Groups participation