Sr. Associate Data Engineer

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 processingBe a key team member that assists in design and development of the data pipelineCreate data pipelines and ensure data quality by implementing ETL processes to migrate and deploy data across systemsContribute to the creation of metric dashboards, self-serve analytics, and business insights using Tableau or Power BIDevelop and maintain data models, data dictionaries, and other documentation to ensure data accuracy and consistencyLeverage cloud platforms (AWS preferred) to build scalable and efficient data solutionsAdhere to best practices for coding, testing, and designing reusable code/componentExploratory data analysis, understand business knowledge, do feature engineeringSupport generation of annual product review documents, regulatory inspections, and process documentationWork 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 fieldExperience 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 processingHands on experience with various Python/R packages for EDA, feature engineering and machine learning model trainingProficiency in data analysis tools (eg. SQL) and experience with data visualization toolsProficiency with data visualization platforms like Tableau, Power BI, or matplotlib/seaborn for PythonExcellent 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 developmentStrong understanding of data modeling, data warehousing, and data integration conceptsInterest 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 skillsStrong communication and collaboration skillsDemonstrated awareness of how to function in a team settingDemonstrated presentation skills

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