This role pays more than
62%
of similar roles. Most pay
$159,000–$223,037
— the shaded band above.
At the midpoint, this role pays about
$205k
versus about
$191k
for comparable roles.
Based on 240 similar postings.
Employer
About AbbVie
AbbVie is a global biopharmaceutical company focused on discovering and delivering innovative medicines and solutions in immunology, oncology, neuroscience, and eye care. Its products include Humira, Skyrizi, and Rinvoq.
AbbVie currently has
353 open roles
on FindRole.
Listed pay typically runs
$109,500–$208,500
across 320 roles with salary data.
The Principal Data Architect II, Biotherapeutics and Genetic Medicine joins the Discovery Research organization to shape a cloud-native data foundation for predictive and generative AI/ML solutions in scientist workflows. This individual contributor role involves designing scalable data models and integration patterns that connect laboratory data across dozens of assays while establishing certified datasets for machine learning development and production deployment. The successful candidate will partner with wet lab scientists, automation engineers, and software teams to advance FAIR data practices and cloud-first architecture principles. Required expertise includes extensive experience in data architecture, data modeling, and infrastructure on AWS, Azure, or GCP. Technical proficiency in SQL, Python, or Java is essential for building robust pipelines. The role addresses the challenge of integrating complex scientific data from modalities like monoclonal antibodies and AAV into a unified, scalable platform.
Define and drive the architecture for a scalable, cloud-native data platform to support AI/ML strategies.
Design data models and integration patterns to connect datasets across multiple laboratory groups.
Establish certified datasets for downstream scientific research, operational use, and machine learning development.
Partner with wet lab scientists and automation engineers to maximize value from automated workflows.
Ensure data pipelines effectively support both model development and production deployment.
Advance FAIR data practices and data stewardship in alignment with organizational priorities.
Champion "data-as-a-product" and cloud-first architecture principles across the organization.
Communicate platform impact through user stories, metrics, and KPIs to demonstrate value to the pipeline.
What we're looking for
MS with 14+ years or PhD with 8+ years in machine learning, computer science, applied mathematics, data science, computational biology, or a related field.
Graduate degree in computer science, data science, computational biology, computational chemistry, computational biophysics, or a related field.
At least 6 years of experience in data architecture after graduate studies with a track record of designing enterprise data platforms.
Experience building cloud data infrastructure on AWS, Azure, or GCP.
Production programming experience in SQL, Python, or Java.
Strong technical skills in data modeling, integration, storage solutions, pipelines, and AI/ML integration.
Experience in the pharmaceutical or biotechnology industry.
Experience leading cross-functional technical teams and working in large R&D environments (preferred).
Data Architecture
PostgreSQL
AWS
SQL
Data Modeling
Data Governance
DataOps
Time-Series Data
Big Data
Machine Learning
AI
Data Warehousing
Data Engineering
Metadata Management
Distributed Query Engines
Data Architecture
Database Design
Data Governance
Data Visualization
Software Engineering Management
Data Standards
Performance Metrics
Cyber Operations