Senior Associate Data Analytics
7 days ago
Department:TBD
Role GCF: 4
Hiring Manager:TBD
Role Description
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.
Objectives of this Role
- 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.
Basic Qualifications
- 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.)
Preferred Qualifications
- 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.
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