Principal Data Engineer, Biologics Discovery
Listed on 2026-10-01
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IT/Tech
Data Engineering, Data Analyst
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, and solutions are personal.
Through our expertise in Innovative Medicine and Med Tech, 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.
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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 FunctionData Analytics & Computational Sciences
Job Sub FunctionData Engineering
Job CategoryScientific/Technology
All Job Posting LocationsRaritan, New Jersey, United States of America, Spring House, Pennsylvania, United States of America, Titusville, New Jersey, United States of America
Job DescriptionOur 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.
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About the opportunityJohnson & 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 mattersHigh-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 SummaryAs 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…
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