Career Category
Information Systems
Job Description
Role Description:
In this role, you will serve as a contributor to Amgenās Global Supply Chain Analytics team, assisting in the development of data and AI-powered products within the distribution sector. Responsibilities include designing, building, maintaining, analyzing, and interpreting data to generate actionable insights for business decision-making. This position requires working with large datasets, developing reports, supporting data governance initiatives, and visualizing data to ensure accessibility, reliability, and efficient management. Candidates should possess technical skills, experience with big data technologies, and knowledge 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:
- Masterās degree and 5 to 8 years of Computer Science, IT or related field experience OR
- Bachelorās degree and 5 to 8 years of Computer Science, IT or related field experience OR
- Diploma and 5 to 8 years of Computer Science, IT or related field experience
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
.