Data Engineering Professional I
Core
Design, analyze, and implement complex manufacturing data-driven solutions to improve product quality, reduce loss, and increase efficiency in global manufacturing and supply operations.
Role type
Data Engineer (Manufacturing/Supply Chain)
Builds
Scalable data pipelines, data models, and analytics solutions for manufacturing processes.
Domain
Pharmaceutical manufacturing and global supply chain
Required skills
SQL, data modeling, Databricks, AWS native technologies, relational databases, batch-based manufacturing processes, Shop-Floor systems (MES, ERP, LIMS, Historian), DevSecOps, automated testing
Preferred skills
Biovia Discoverant, Simca Online, PAS-X Savvy, Siemens gPROMS, Computer Systems Validation GAMP, Data Science workflows (Machine Learning/Deep Learning), AWS (S3, EC2, Terraform)
Technologies
AWS, Databricks, Oracle, MongoDB, SQL
Responsibilities
Contribute to data engineering of existing and new IT systems; Enable data analytics (process trending, modeling, real-time, predictive) in a GxP environment; Develop and maintain scalable data pipelines; Drive identification and resolution of technical issues; Ensure Digital Products and Platforms are built efficiently and on state-of-the-art technology; Provide guidance to business partners on complex technical changes; Collaborate with analytics and business teams to improve data models for business intelligence.
Seniority
Mid-level (3+ years experience)