Sr. Associate Data Engineer

Career Category Information Systems Job Description ABOUT AMGEN Amgen harnesses the best of biology and technology to fight the world’s toughest diseases, and make people’s lives easier, fuller and longer. We discover, develop, manufacture and deliver innovative medicines to help millions of patients. Amgen helped establish the biotechnology industry more than 40 years ago and remains on the cutting-edge of innovation, using technology and human genetic data to push beyond what’s known today. ABOUT THE ROLE Role Description: As part of the cybersecurity organization, the Data Engineer is responsible for designing, building, and maintaining data infrastructure to support data-driven decision-making. This role involves working with large datasets, developing reports, executing data governance initiatives, and ensuring data is accessible, reliable, and efficiently managed. Th e role sits at the intersection of data infrastructure and business insight delivery, requiring the Data Engineer to design and build robust data pipelines while also translating data into meaningful visualizations for stakeholders across the organization. The ideal candidate has strong technical skills, experience with big data technologies, and a deep understanding of data architecture, ETL processes, and cybersecurity data frameworks. 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 . Develop and maintain interactive dashboards and reports using tools like Tableau, ensuring data accuracy and usability Schedule and manage workflows the ensure pipelines run on schedule and are monitored for failures. Collaborate with cross-functional teams to understand data requirements and design solutions that meet business needs . Develop and maintain data models, data dictionaries, and other documentation to ensure data accuracy and consistency . Implement data security and privacy measures to protect sensitive data . Leverage cloud platforms (AWS preferred) to build scalable and efficient data solutions . Collaborate and communicate effectively with product teams . Collaborate with data scientists to develop pipelines that meet dynamic business needs . Share and discuss findings with team members practicing SAFe Agile delivery model. Functional Skills: Basic Qualifications: Master’s degree OR Bachelor’s degree and 5 to 9 years of Computer Science, IT or related field experience Preferred Qualifications: Hands on experience with data practices, technologies, and platforms, such as Databricks, Python, Gitlab, LucidChart , etc . Proficiency in data analysis tools ( e . g. 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 best practices 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 Strong understanding of data modeling, data warehousing, and data integration concepts Experience with data visualization and dashboarding tools—Tableau, Power BI, or similar is a plus Knowledge of Python/R, Databricks, cloud data platforms Experience working in Product team's environment Experience working in an Agile environment Professional Certifications: AWS Certified Data Engineer preferred Databricks Certificate preferred Soft Skills: Initiative to explore alternate technology an