Career CategoryInformation SystemsJob DescriptionRole Description:This role is a key part of Amgen’s Global Supply Chain Analytics team, developing data and AI-driven solutions for customer service. 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 analyticsBasic Qualifications and Experience:Master’s degree and 5 to 8 years of Computer Science, IT or related field experience ORBachelor’s degree and 5 to 8 years of Computer Science, IT or related field experience ORDiploma and 5 to 8 years of Computer Science, IT or related field experienceFunctional 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 datasetsGood-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 interfacesProfessional Certifications:Certified Data & Analytics professionalSoft Skills:Excellent critical-thinking and problem-solving skillsStrong communication and collaboration skillsDemonstrated awareness of how to function in a team settingDemonstrated presentation skills.