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

Come to work each day with an inclusive and collaborative Business technology team! As a Data Engineer in AbbVie Business Technology Solutions (BTS), you’ll have opportunities to contribute to the digital transformation of a leading biopharma company, helping to create solutions that impact patients and their communities for the better. 

***This is a hybrid role based in Lake County, IL***       

We are seeking a curious, creative, and business-oriented Data Engineer to join our BTS US Commercial BTS team. The ideal candidate will possess strong analytical skills and a deep affinity for analysis, math, and statistics. In addition to expertise in quantitative methodologies and programming, a keen business acumen is essential. A passion for data exploration, machine learning, and innovative thinking is crucial. Staying updated with leading-edge data engineering technologies and utilizing relevant technical skills and methodologies are key aspects of this role. 

Responsibilities 

• Demonstrate a deep understanding of data concepts, analytics, complex data structures, and relationships. 

• Create and maintain comprehensive system and project documentation, including change requests, functional requirements, test plans, data migration plans, and cutover plans. Delegate appropriate tasks to junior analysts. 

• Review and refine data models for development projects, assisting team members in understanding and adhering to established standards. 

• Partner with key stakeholders and external vendors/partners to maintain, optimize, scale, and operationalize existing machine learning models. 

• Establish trust wit