Principal Data Engineer, Biologics Discovery

Johnson Johnson; Pennsylvania; On-site; USD 150,000 - 190,000; Full time

Job summary

Johnson & Johnson Innovative Medicine is hiring a Principal Data Engineer for the Biologics Discovery group. You will shape discovery data products, data models, and schemas to enable AI-ready analytics and ML workflows. You’ll collaborate with scientists and AI/ML teams to deliver durable data assets across cloud platforms.

You will lead data standards, governance, and interoperability, ensuring trusted data products scale across enterprise partnerships and forthcoming AI initiatives.

Qualifications

• Degree in Computer Science, Data Science, Engineering, or a related computational field.
• 8+ years (Bachelor's), 5+ years (Master's), or 3+ years (Ph.D.) of experience designing and delivering data products, data models, and analytics-ready datasets within pharmaceutical, biotechnology, or life sciences organizations.
• Deep proficiency in Python and SQL, with hands-on experience designing and implementing reusable and scalable data assets on cloud data platforms (e.g., Snowflake, AWS, Azure, BigQuery) to support analytics, machine learning, and AI-driven workflows.
• Experience applying FAIR data principles, metadata management, controlled vocabularies, data lineage, and provenance practices in scientific data environments.
• Demonstrated technical leadership through architecture reviews, mentorship, code reviews, or leadership of complex technical initiatives.
• Proven ability to lead complex cross-functional technical initiatives and establish data standards across multiple stakeholder groups.

Responsibilities

• Design and deliver AI-ready discovery data products that support ML, AI, and insight generation across Biologics Discovery.
• Define and lead the delivery of scalable integration requirements, transformation patterns, and data schemas that support discovery data acquisition, harmonization, and downstream analytics.
• Translate scientific and analytical requirements from discovery teams into data product specifications, data contracts, acceptance criteria, and delivery requirements.
• Define access and data consumption patterns that enable analytics, modeling, and agentic AI workflows, aligned with industry data standards and frameworks.
• Catalog discovery instruments, data types, and data sources to inform data product prioritization and sustainable integration approaches.
• Establish, champion, and drive adoption of standards and best practices for discovery data products, including data quality, provenance, lineage, reproducibility, metadata, and documentation.
• Partner with ontology, data architecture, platform, and AI teams to ensure discovery data products are connected, discoverable, and suitable for advanced analytics, ML, and agentic AI applications.

Skills

Python

SQL

Snowflake

AWS

Azure

BigQuery

Data modeling

Data governance

Education

Bachelor's degree in Computer Science

Master's degree in Data Science

PhD in a related field

Tools

Snowflake

AWS

Azure

BigQuery

Job description

At Johnson & Johnson,we believe health is everything. Our strength in healthcare innovation empowers us to build aworld where complex diseases are prevented, treated, and cured,where treatments are smarter and less invasive, andsolutions are personal.Through our expertise in Innovative Medicine and MedTech, we are uniquely positioned to innovate across the full spectrum of healthcare solutions today to deliver the breakthroughs of tomorrow, and profoundly impact health for humanity.Learn more at jnj.com.

As guided by Our Credo, Johnson & Johnson is responsible to our employees who work with us throughout the world. We provide an inclusive work environment where each person is considered as an individual. At Johnson & Johnson, we respect the diversity and dignity of our employees and recognize their merit.

Job Function

Data Analytics & Computational Sciences

Job Sub Function

Data Engineering

Job Category

Scientific/Technology

All Job Posting Locations

Raritan, New Jersey, United States of America, Spring House, Pennsylvania, United States of America, Titusville, New Jersey, United States of America

Job Description

Our expertise in Innovative Medicine is informed and inspired by patients, whose insights fuel our science-based advancements. Visionaries like you work on teams that save lives by developing the medicines of tomorrow.

Join us in developing treatments, finding cures, and pioneering the path from lab to life while championing patients every step of the way.

Learn more at https://www.jnj.com/innovative-medicine

About the opportunity

Johnson & Johnson Innovative Medicine is seeking a Principal Data Engineer dedicated to our Biologics Discovery organization. This is a high-leverage role responsible for shaping how discovery data is structured, connected, and made AI-ready across Biologics Discovery. The role serves as the bridge between scientific workflows, data consumers, and technology partners, ensuring that discovery data products support scientific research, analytics, machine learning, and agentic workflows.

This position will be based at one of our office locations in either Spring House, PA (strongly preferred), Titusville, NJ, or Raritan, NJ. (No remote option.)

Why this role matters

High-quality, well-governed scientific data is foundational to our vision for AI-enabled biologics discovery. This role provides senior technical leadership within Biologics Discovery, translating scientific needs into data products, scientific data models, and requirements, and working with enterprise data and technology partners to ensure discovery data is trusted, connected, and AI-ready as the broader ecosystem evolves.

Position Summary

As a Principal Data Engineer, you will lead the design of discovery data products, scientific data models (schemas, entities, and relationships), and integration requirements that enable discovery data to be acquired, connected, harmonized, and delivered across the Biologics Discovery ecosystem. You will work closely with scientists and AI/ML teams to translate their needs into durable, reusable, and AI-ready data assets.

Working in close partnership with enterprise Data Strategy & Products and Technology teams, you will ensure discovery data needs are represented in enterprise standards and that those standards are effectively applied within Biologics Discovery. You will help shape the future-state discovery data ecosystem while delivering near-term value through trusted data products, harmonized data, and metadata practices that support long-term interoperability and reuse.

Key Responsibilities

Discovery Data Products & Integration

• Design and deliver AI-ready discovery data products that support ML, AI, and insight generation across Biologics Discovery, applying agile delivery practices to respond to evolving scientific needs.
• Define and lead the delivery of scalable integration requirements, transformation patterns, and data schemas that support discovery data acquisition, harmonization, and downstream analytics, working with scientific, data, and technology stakeholders to enable reliable data exchange across systems.
• Translate scientific and analytical requirements from discovery teams into data product specifications, data contracts, acceptance criteria, and delivery requirements, in partnership with scientists, AI/ML teams, and technology partners.
• Define access and data consumption patterns that enable analytics, modeling, and agentic AI workflows, aligned with industry data standards and frameworks.
• Catalog discovery instruments, data types, and data sources to inform data product prioritization and sustainable integration approaches.

Data Stewardship & Organizational Impact

• Establish, champion, and drive adoption of standards and best practices for discovery data products, including data quality, provenance, lineage, reproducibility, metadata, and documentation.
• Partner with ontology, data architecture, platform, and AI teams to ensure discovery data products are connected, discoverable, and suitable for advanced analytics, ML, and agentic AI applications.
• Apply FAIR data principles, so data products are reusable, scalable, and interoperable.
• Serve as a thought leader in scientific data architecture, harmonization, and AI-ready data practices across the organization.

Qualifications

Required

• Degree in Computer Science, Data Science, Engineering, or a related computational field.
• 8+ years (Bachelor's), 5+ years (Master's), or 3+ years (Ph.D.) of experience designing and delivering data products, data models, and analytics-ready datasets within pharmaceutical, biotechnology, or life sciences organizations.
• Deep proficiency in Python and SQL, with hands‑on experience designing and implementing reusable and scalable data assets on cloud data platforms (e.g., Snowflake, AWS, Azure, BigQuery) to support analytics, machine learning, and AI-driven workflows.
• Experience applying FAIR data principles, metadata management, controlled vocabularies, data lineage, and provenance practices in scientific data environments.
• Demonstrated technical leadership through architecture reviews, mentorship, code reviews, or leadership of complex technical initiatives.
• Proven ability to lead complex cross‑functional technical initiatives and establish data standards across multiple stakeholder groups.
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