Process Analytics 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

The Data Engineer acts as both a hands-on builder and a technical leader, designing, building, and optimizing data pipelines and models to support reliable, efficient and standardized bioprocess improvement advanced analytics. This role translates business requirements into robust, scalable data structures and workflows, ensuring quality, compliance, and performance. As a technical leader, the Data Engineer defines and guides data strategy, establishes execution roadmaps, and mentors other team members.  

Responsibilities

• Provide technical leadership in designing, developing, and maintaining conceptual, logical, and physical data models, architecting and optimizing ELT pipelines and database structures including tables, data types, indexes, keys, and join logic 
• Define and implement data strategies, architectural standards, best practices, coding standards, and governance frameworks 
• Guide and coach engineering teams in the implementation and optimization of scalable data solutions, ensuring alignment with enterprise strategy 
• Translate business needs into effective data architectures, workflows, and products in collaboration with cross-functional teams, including data architects and engineers 
• Manage metadata, maintain data lineage, oversee compliance initiatives, and lead efforts in quality improvement, integrity checks, and duplicate detection 
• Conduct data model reviews, document specifications, and communicate technical roadmaps to stakeholders 
• Lead implementation of automated data validation, unit testing, and deployment workflows, promoting agile and CI/CD methodologies 
• Apply advanced data governance practices to reduce redundancy, optimize scalabilit