Amgen operates a massive biotech R&D and manufacturing footprint with 10,000+ employees across 22 countries. The hiring mix reveals a data-heavy organization (93 active data roles) coupled with 68 engineering positions and significant research/manufacturing headcount — typical of a company shifting from traditional pharma workflows toward integrated MLOps pipelines and master-data management. Current pain points (data integration, inspection readiness, compliance, statistical programming gaps) align with active projects in MLOps pipeline development, MDM implementation, and lab digitization, indicating a multi-year infrastructure modernization effort.
Notable leadership hires: Medical Director, Data Governance Lead, Director GSC operations, Therapeutic Area Lead, Regulatory Lead
Amgen is a publicly traded biotechnology company headquartered in Thousand Oaks, California, with operations across manufacturing, research, and commercialization. The company develops medicines across oncology, cardiovascular disease, osteoporosis, inflammatory conditions, and rare diseases. Its tech stack spans pharma-specific platforms (Veeva Vault, Benchling) alongside enterprise systems (SAP, Oracle, ServiceNow) and cloud infrastructure (AWS, Databricks). Current adoption of Workday, OneStream, and SAP S/4HANA—while retiring legacy SAP ECC—signals a transition toward unified financial and workforce systems. The organization maintains active hiring across data, engineering, research, and operations globally, with senior roles concentrated in medical direction, regulatory affairs, and data governance.
Amgen uses Veeva Vault, Oracle, SAP, AWS, Databricks, Apache Kafka, Benchling, ServiceNow, and Workday. Currently adopting SAP S/4HANA and OneStream while phasing out legacy SAP ECC.
Active initiatives include MLOps pipeline development, master-data management implementation, lab digitization and electronic recipe management, complex statistical analysis of clinical studies, and technology transfer across regions.
Amgen's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.