Senior Data Engineer

Company Description

AbbVie's mission is to discover and deliver innovative medicines and solutions that solve serious health issues today and address the medical challenges of tomorrow. We strive to have a remarkable impact on people's lives across several key therapeutic areas – immunology, oncology, neuroscience, and eye care – and products and services in our Allergan Aesthetics portfolio. For more information about AbbVie, please visit us at www.abbvie.com. Follow @abbvie on X, Facebook, Instagram, YouTube, LinkedIn and Tik Tok.

Job Description

Purpose

A team of data scientists with a unique blend of Business, Scientific, and Machine Learning expertise who seek to: Unleash the full potential of AbbVie’s data assets by bringing technology and/or data and insights to the forefront of decision making via fit-for-purpose data analytics solutions. Broaden the scope and impact of Analytics and Data Science by constantly exploring new opportunities to transform clinical development and R&D. Collaborate with stakeholders to outline the problem, explore solutions, refine opportunities and deliver a product with a continuous innovation mindset"

Responsibilities

• Collaborates with the Data Scientists and cross-functional data stewards to identify appropriate data sources and to enable streamlined data flow for the Data Science and Analytics capabilities across clinical development.
• Develop, construct, test and maintain architectures (such as databases and large-scale process systems) to support strategic projects with in Clinical Development
• Build data products and service processes which perform data transformation, metadata extraction, workload management and error processing management
• Implement standardized, automated operational and quality control processes to deliver accurate and timely data and reporting
• Adhere to best practices for coding, testing and designing reusable code/component
• Contribute to the discovery and understanding of new tools, and techniques and propose improvements to the data pipeline
• Develop data set processes for data modeling, mining and production
• Develop solutions to improve data reliability, efficiency and quality
• Ensures adherence to federal regu