Overview

Amgen harnesses the best of biology and technology to fight the world’s toughest diseases, and make people’s lives easier, fuller and longer.

Responsibilities

• The Sr. Data Engineer is responsible for designing, building, maintaining, analyzing, and interpreting data to provide actionable insights that drive business decisions. This role involves working with large datasets, developing reports, supporting and executing data governance initiatives and, visualizing data to ensure data is accessible, reliable, and efficiently managed. The ideal candidate has strong technical skills,
• experience with big data technologies, and a deep
• understanding of data architecture and ETL processes Roles &
• 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 design, development, and implementation of data pipelines, ETL/ELT processes, and data integration solutions
• Take ownership of data pipeline projects from inception to deployment, manage scope, timelines, and risks
• 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 with Data Architects, Business SMEs, and Data Scientists to design and develop end-to-end data pipelines to meet fast paced business needs across geographic regions
• Identify and resolve complex data-related challenges
• Adhere to best practices for coding, testing, and designing reusable code/component
• Explore new tools and technologies that will help to improve ETL platform performance
• Participate in sprint planning meetings and provide estimations on technical implementation
• Collaborate and communicate effectively with product teams

Qualifications

• Master’s /Bachelor’s degree with 9-12 years of experience in Computer Science, IT or related field
• Hands on experience with big data technologies and platforms, such as Databricks, Apache Spark (PySpark, SparkSQL), workflow orchestration, performance tuning on big data processing
• Hands on experience with various Python/R packages for data analysis, feature engineering and machine learning model training
• Proficiency in data analysis tools (eg. SQL) and experience with data visualization tools
• Excellent problem-solving skills and the ability to work with large, complex datasets
• Strong understanding of data governance frameworks, tools, and best practices.
• Knowledge of data protection regulations and compliance requirements (e.g., GDPR, CCPA)
• Delta Lake, DataFrames, broadcast join
• 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
• Knowledge of Python/R, Databricks, SageMaker, cloud data platforms
• Experience with Clinical Development domain.
• Certified Data Engineer / Data Analyst (preferred on Databricks or cloud environments)
• Machine Learning Certification (preferred on Databricks or Cloud environments)
• SAFe for Teams certification (preferred)
• 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