Principal Data Architect II - Biotherapeutics and Genetic Medicine

Company Description

About AbbVie

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 including immunology, oncology and neuroscience - and products and services in our Allergan Aesthetics portfolio. For more information about AbbVie, please visit us at www.abbvie.com. Follow @abbvie on LinkedIn, Facebook, Instagram, X and YouTube.

Job Description

Position overview: 

Biotherapeutics and Genetic Medicine (BGM) sits within AbbVie’s Discovery Research organization and supports discovery and optimization across biotherapeutic and genetic medicine modalities, including monoclonal antibodies, multispecifics, proteins, conjugates, AAV, LNPs, and siRNA.  

The Principal Data Architect will shape the cloud-native data foundation that enables predictive and generative AI/ML solutions in discovery scientist workflows. This role owns the architecture, adoption, and continuous improvement of a scalable data platform that connects laboratory data across dozens of assays, supports machine learning development and deployment, and improves how scientific data is used across the organization.  

The position reports to the Head of AI/ML in BGM and serves as a trusted advisor to senior leadership. This is a technical leadership role on the individual contributor track, with potential to expand into people management in the future. It requires close partnership with wet lab scientists, ML engineers, software engineers, data engineers, automation teams, and data governance partners. The role is central to building a robust, resilient, and scalable data foundation for BGM’s AI/ML strategy. 

Responsibilities: 

• Define and drive the architecture for a scalable, cloud-native data platform that supports AbbVie’s AI/ML strategy in BGM. 
• Design data models and integration patterns that connect datasets generated across multiple lab groups and establish certified datasets for downstream scientific, operational, and machine learning use. 
• Partner with wet lab scientists and automation engineers to maximize the value of data captured through lab automation workflows. 
• Work with data scientists and deployment engineers to ensure data pipelines support both model development and production deployment. 
• Advance FAIR data practices and data stewardship in alignment with BGM strategic priorities. 
• Champion connected data, data-as-a-product, and cloud-first architecture principles across the organization. 
• Partner with data infrastructure and governance experts to ensure data policies are implemented effectively. 
• Align BGM data infrastructure initiatives with broader AbbVie efforts such as Convergence and ARCH. 
• Communicate platform impact through user stories, metrics, and KPIs that show the value of the data platform to AbbVie’s therapeutic program pipeline. 

Qualifications

• MS with 14+ years’ or PhD with 8+ years’ experience in machine learning, computer science, applied mathematics, data science, computational biology, or a closely related field. 
• 6+ years of experience in data architecture after completion of graduate studies, with a track record of designing enterprise data platforms 
• Graduate degree in computer science, data science, computational biology, computational chemistry, computational biophysics, or a related field. 
• Experience designing enterprise data platforms. 
• Strong technical skills in data modeling, data integration, data storage solutions, data pipelines, and AI/ML integration. 
• Production programming experience in SQL, Python, or Java. 
• Experience building cloud data infrastructure on AWS, Azure, or GCP. 
• Ability to work across wet lab and dry lab scientific workflows. 
• Experience collaborating across functions and building stakeholder alignment. 
• Strong communication and interpersonal skills. 
• Ability to apply data governance principles in day-to-day decision-making. 
• Experience in the pharmaceutical or biotechnology industry. 

Preferred: 

• Experience leading cross-functional technical teams across reporting lines and multiplying their impact through best prac