Senior Cloud Data Architect for AI/ML Platforms

BioSpace; Worcester (MA); On-site; USD 150,000 - 210,000; Full time

Job summary

AbbVie in Worcester, MA seeks a Principal Data Architect to shape a cloud-native data foundation enabling predictive and generative AI/ML in discovery scientist workflows. You will own the architecture, adoption, and continuous improvement of a scalable data platform that connects laboratory data across assays and supports model development and production deployment.

The role collaborates with wet lab scientists, ML engineers, software engineers, data engineers, automation teams, and governance

Qualifications

• MS with 14+ years or PhD with 8+ years in machine learning, computer science, data science, or related field.
• 6+ years of experience in data architecture with enterprise data platforms.
• Graduate degree in computer science, data science, or related field.
• Experience designing enterprise data platforms.
• Production programming in SQL, Python, or Java.

Responsibilities

• Define and drive the architecture for a scalable, cloud-native data platform.
• Design data models and integration patterns connecting lab datasets.
• Collaborate with wet lab scientists and automation engineers to maximize data value.
• Ensure data pipelines support model development and production deployment.
• Advance FAIR data practices and data stewardship.
• Champion data-centric, cloud-first architecture across the organization.
• Coordinate with data governance and architecture teams to enforce policies.
• Align data infrastructure initiatives with broader AbbVie programs like Convergence and ARCH.
• Communicate platform impact through metrics and KPIs.

Skills

Data architecture

Cloud data platforms

Data modeling

Data integration

AI/ML integration

SQL

Python

Java

AWS

Azure

GCP

Communication

Education

MS in computer science or related field

PhD in related field (preferred)

Tools

AWS

Azure

GCP

Job description

AbbVie in Worcester, MA seeks a Principal Data Architect to shape a cloud-native data foundation enabling predictive and generative AI/ML in discovery scientist workflows. You will own the architecture, adoption, and continuous improvement of a scalable data platform that connects laboratory data across assays and supports model development and production deployment.

The role collaborates with wet lab scientists, ML engineers, software engineers, data engineers, automation teams, and governance