Principal Data Engineer, Biologics Discovery — AI-Ready

Johnson & Johnson; Spring House (PA); On-site; USD 117,000 - 201,000; Full time

Job summary

Johnson & Johnson Innovative Medicine seeks a Principal Data Engineer to shape discovery data products and data models across Biologics Discovery. You will connect scientific workflows with data platforms, delivering AI-ready assets for analytics and ML initiatives.

You will collaborate with scientists, AI/ML teams, and technology partners to ensure data is reusable, interoperable, and governed, while guiding standards and best practices across the organization.

Qualifications

• Degree in Computer Science, Data Science, Engineering or related field.
• 8+ years (Bachelor's), 5+ years (Master's), or 3+ years (Ph.D.) delivering data products and analytics-ready datasets in pharma/biotech.
• Proficiency in Python and SQL, with cloud data platforms (Snowflake/AWS/Azure/BigQuery).
• Experience applying FAIR data principles, metadata management, data lineage and provenance.

Responsibilities

• Design AI-ready discovery data products for ML/AI insights.
• Lead scalable integration, transformation patterns, and data schemas for discovery data.
• Translate scientific needs into data product specs, contracts, and acceptance criteria.
• Define data access patterns for analytics and agentic AI workflows.
• Catalog data sources to inform prioritization and integration approaches.

Skills

Python

SQL

Data modeling

Leadership

Communication

Education

Degree in Computer Science, Data Science, Engineering

Tools

Snowflake

AWS

Azure

BigQuery

Job description

Johnson & Johnson Innovative Medicine seeks a Principal Data Engineer to shape discovery data products and data models across Biologics Discovery. You will connect scientific workflows with data platforms, delivering AI-ready assets for analytics and ML initiatives.

You will collaborate with scientists, AI/ML teams, and technology partners to ensure data is reusable, interoperable, and governed, while guiding standards and best practices across the organization.