Principal Data Architect II, Biotherapeutics and Genetic Medicine

AbbVie•Worcester, MA

12d•$141,500 - $268,500•Hybrid

About The Position

AbbVie's Biotherapeutics and Genetic Medicine (BGM) organization, within Discovery Research, focuses on the discovery and optimization of biotherapeutic and genetic medicine modalities. These include monoclonal antibodies, multispecifics, proteins, conjugates, AAV, LNPs, and siRNA. The Principal Data Architect will be instrumental in shaping the cloud-native data foundation necessary for advanced predictive and generative AI/ML solutions within discovery scientist workflows. This role is responsible for the architecture, adoption, and ongoing enhancement of a scalable data platform. This platform will connect laboratory data from numerous assays, facilitate machine learning development and deployment, and improve the utilization of scientific data across the organization. The position reports to the Head of AI/ML in BGM and acts as a key advisor to senior leadership. It is a technical leadership role on the individual contributor track, with potential for future expansion into people management. Collaboration with wet lab scientists, ML engineers, software engineers, data engineers, automation teams, and data governance partners is essential. The role is critical for establishing a robust, resilient, and scalable data foundation to support BGM's AI/ML strategy.

Requirements

MS with 14+ years’ or PhD with 8+ years’ 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.

Nice To Haves

Experience leading cross-functional technical teams across reporting lines and multiplying their impact through best practices.
Experience working in large, cross-functional R&D environments.

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.