Job
Description
What you will do Lets do this. Lets change the world. In this vital role you will play a key role in a regulatory submission content automation initiative which will modernize and digitize the regulatory submission process, positioning Amgen as a leader in regulatory innovation. The initiative brings to bear innovative technologies, including Generative AI, Structured Content Management, and integrated data to automate the creation, review, and approval of regulatory content. The role is responsible for sourcing and analyzing data for this initiative and support designing, building, and maintaining the data pipelines to drive business actions and automation. This role involves working with Operations source systems, find the right data sources, standardize datasets, supporting data governance to ensure data is accessible, reliable, and efficiently managed. The ideal candidate has deep technical skills, experience with big data technologies, and a deep understanding of data architecture and ETL processes. Roles & Responsibilities: Contribute to the design, development, and implementation of scalable data pipelines, ETL/ELT processes, and data integration solutions. Schedule and manage workflows to ensure pipelines run on time and are monitored for failures. Implement data integration solutions and manage end-to-end pipeline projects, including scope, timelines, and risk. Identify, extract, and integrate required business data from operations systems residing in modern cloud-based architectures. Reverse-engineer schemas and explore source system tables to map local representations of target business concepts. Break down information models into fine-grained, business-contextualized data components. Navigate application UIs and backends to gain business domain knowledge and detect data inconsistencies. Work closely with Enterprise Data Lake delivery and platform teams to align applications with architectural and development guidelines. Collaborate with data scientists to develop pipelines that meet dynamic business needs across regions. Leverage cloud platforms (AWS, Databricks preferred) to build scalable and efficient data solutions. Familiarity with code versioning using Git, Jenkins, and code migration tools. Stay up to date with the latest data technologies and trends. Adhere to SOPs, GDEs, and standard methodologies for coding, testing, and reusable component design. Keen on embracing new responsibilities, facing challenges, and mastering new technologies. What we expect of you We are all different, yet we all use our unique contributions to serve patients. Basic Qualifications: Masters degree in computer science or engineering field and 0 to 1 years of relevant experience OR Bachelors degree in computer science or engineering field and 1 to 3 years of relevant experience OR Diploma and Minimum of 5+ years of relevant work experience Functional Skills: Must-Have Skills: Hands on experience with data practices, technologies, and platforms, such as Databricks, Python, Prophecy, Gitlab, LucidChart etc Proficiency in data analysis tools (eg. SQL) and experience with data sourcing tools Excellent problem-solving skills and the ability to work with large, complex datasets Understanding of data governance frameworks, tools, and standard methodologies. Knowledge of and experience with data standards (FAIR) and protection regulations and compliance requirements (e.g., GDPR, CCPA) Good-to-Have Skills: Experience with ETL tools and various Python packages related to data processing, machine learning model development Good understanding of data modeling, data warehousing, and data integration concepts Knowledge of Python/R, Databricks, cloud data platforms Professional Certifications Certified Data Engineer / Data Analyst (preferred on Databricks) Soft Skills: Excellent critical-thinking and problem-solving skills Good communication and collaboration skills Demonstrated awareness of how to function in a team setting Demonstrated presentation skills
