Senior Associate Data Analytics

Department:TBD
Role GCF: 4
Hiring Manager:TBD

This role will play a key part in supporting Amgens Tech & Workforce Strategy by designing and building robust, scalable data pipelines that enable advanced analytics and insights.

We are seeking an expert-level data engineer who is eager to gain exposure to the business/FP&A side of Biotech. You bring the data engineering masterywell teach you the business context. This is a rare opportunity to grow your career at the intersection of cutting-edge engineering and strategic business decision-making.

Please be aware that Amgens Tech & Workforce Strategy is a key strategic initiative to ensure Amgens future success. Its a very fast-moving, start-up environment and we need staff that are adaptable to rapidly evolving work priorities and a willingness to be flexible with work hours to get the job done.

• Develop, optimize, and maintain scalable data pipelines using Prophecy and Databricks.
• Design and implement robust data models and frameworks to support enterprise-wide analytics.
• Partner closely with business stakeholders to understand requirements and translate them into technical solutions.
• Ensure data quality, consistency, and reliability across critical datasets.
• Continuously improve data engineering practices to enhance performance, scalability, and maintainability.

• Masters degree and 2 years of relevant experienceOR
• Bachelors degree and 1 year of relevant experienceOR
• Associates degree and 4 years of relevant experienceOR
• High school diploma/GED and 8 years of relevant experience
• (Experience should be in data engineering, software engineering, or related fields.)

• 4+ years of experience in data engineering, with a strong focus on pipeline design and optimization.
• Expert-level proficiency in Python and SQL, with hands-on Databricks experience.
• Experience building production-grade ETL/ELT pipelines with large, complex datasets.
• Familiarity with data orchestration tools such as Airflow, Prophecy, or equivalent.
• Strong understanding of data modeling, governance, and performance optimization techniques.
• Exposure to business intelligence tools (e.g., Tableau, Power BI) is a plus, but not required.
• Prior experience in biopharma, biotech, or other data-intensive industries preferred but not required.