Sr. Associate Data Engineer

Career Category

Information Systems

Job Description

ABOUT AMGEN

At Amgen, our mission to serve patients drives everything we do. We discover, develop, manufacture, and deliver innovative medicines, and we use technology, data, and collaboration to help teams across the enterprise operate with greater speed, quality, and impact.

Role Description:

This role is a key part of Amgen’s Global Supply Chain Analytics team, developing data and AI-driven solutions for Supply Chain Business. Responsibilities include designing, building, and managing data, analyzing it for actionable insights, creating reports, supporting data governance, and visualizing information to ensure reliable and efficient data management. The ideal candidate has strong technical skills, experience with big data, and a solid understanding of data architecture and ETL processes.

Roles & Responsibilities:

Design, develop, and maintain data solutions for data generation, collection, and processing

Be a key team member that assists in design and development of the data pipeline

Create data pipelines and ensure data quality by implementing ETL processes to migrate and deploy data across systems

Contribute to the creation of metric dashboards, self-serve analytics, and business insights using Tableau or Power BI

Develop and maintain data models, data dictionaries, and other documentation to ensure data accuracy and consistency

Leverage cloud platforms (AWS preferred) to build scalable and efficient data solutions

Adhere to best practices for coding, testing, and designing reusable code/component

Exploratory data analysis, understand business knowledge, do feature engineering

Support generation of annual product review documents, regulatory inspections, and process documentation

Work with data engineers on data quality assessment, data cleansing and data analytics

Basic Qualifications and Experience:

Bachelor’s or Master’s degree in a relevant field (e.g., Computer Science, Engineering or equivalent).

5–8 years of work experience in Information Technology, Information Systems, or a related field

Experience in the global pharmaceutical industry preferred.

Functional Skills:

Must-Have Skills

Hands on experience with big data technologies and platforms, such as Databricks (PySpark, SparkSQL), workflow orchestration, performance tuning on big data processing

Hands on experience with various Python/R packages for EDA, feature engineering and machine learning model training

Proficiency in data analysis tools (eg. SQL) and experience with data visualization tools

Proficiency with data visualization platforms like Tableau, Power BI, or matplotlib/seaborn for Python

Excellent problem-solving skills and the ability to work with large, complex datasets

Good-to-Have Skills:

Experience with ETL tools such as Apache Spark, and various Python packages related to data processing, machine learning model development

Strong understanding of data modeling, data warehousing, and data integration concepts

Interest in GenAI/LLM technology and building data products that support natural language interfaces

Professional Certifications :

Certified Data & Analytics professional

Soft Skills:

Excellent critical-thinking and problem-solving skills

Strong communication and collaboration skills

Demonstrated awareness of how to function in a team setting

Demonstrated presentation skills

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