Principal Developer, Oncology Data & AI Systems (2 available)

Johnson Johnson; Titusville (NJ); On-site; USD 120,000 - 180,000; Full time

Job summary

Johnson & Johnson Innovative Medicine is recruiting a Principal Developer, Oncology Data & AI Systems to strengthen the AI-ready data foundation for Oncology R&D. You will lead data capture modernization and design scalable pipelines that support high-quality, interoperable datasets for AI/ML.

This role focuses on data science initiatives across Clinical, Pre-Clinical, RWD and omics platforms, enabling trusted datasets and foundational data products that accelerate insights and model

Qualifications

• Bachelor's degree in relevant field required or higher.
• 5+ years of experience in data engineering with data modeling and database architecture.
• Proficiency in Python, R and SQL for data engineering.

Responsibilities

• Partner with Oncology R&D and Data Science stakeholders to identify, prioritize, and deliver high-impact data, AI/ML, and GenAI use cases.
• Own the end-to-end design, build, and lifecycle management of Oncology R&D data products, including requirements, architecture, ETL/ELT development, documentation, and operational support.
• Integrate multi-modal R&D data across biomarker labs, clinical trials, real-world data/evidence, and omics to create trusted, reusable datasets.
• Co-develop an AI-ready data ecosystem with Data Product Engineers, Data Scientists, Knowledge Graph Engineers, EA, and IT teams.
• Translate complex scientific, clinical, and operational needs into scalable engineering solutions ensuring interoperability and standards.
• Design and optimize data pipelines for structured and unstructured data using Python, R, SQL and AWS to improve throughput and reliability.
• Implement data quality and monitoring frameworks with KPI-driven evaluation of data product performance.
• Establish data governance by maintaining data lineage, metadata, versioning, and compliance with internal and regulatory standards.

Skills

Data engineering

Data modeling

Schema design

Education

Bachelor's Degree in Computer Science, Engineering, Life Sciences, or other relevant field

Tools

Python

R

SQL

Job description

At Johnson & Johnson, we believe health is everything. Our strength in healthcare innovation empowers us to build a world 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 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 Science

Job Category:

Scientific/Technology

All Job Posting Locations:

Cambridge, Massachusetts, United States of America, Raritan, New Jersey, United States of America, San Diego, California, 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

Johnson and Johnson Innovative Medicine is recruiting a Principal Developer, Oncology Data & AI Systems (2 available positions) to strengthen the AI-ready data foundation that powers Oncology R&D. This role will lead efforts to modernize and standardize data capture, translate scientific and business needs into engineering requirements, and design, build, and optimize scalable data pipelines and workflows that ensure data is high-quality, well-governed, interoperable, and fit for advanced analytics and AI/ML.

This role focuses on data science initiatives across Oncology R&D- including Clinical, Pre-Clinical, RWD and 'omics platforms by enabling trusted, reusable datasets and foundational data products that accelerate downstream insights and model development. This role will be a leading data science contributor and creative problem solver with developing AI-ready data and other routinely used data applications that improve speed, reliability and impact of data-driven decision making for Oncology R&D.

This position will be located in either Cambridge, MA; Spring House, PA; Titusville, NJ; Raritan, NJ; or San Diego, CA (no remote option).

Key Responsibilities:

• Partner with Oncology R&D and Data Science stakeholders to identify, prioritize, and deliver high-impact data, AI/ML, and GenAI use cases that accelerate scientific discovery, study execution, and evidence generation.
• Own the end-to-end design, build, and lifecycle management of Oncology R&D data products , including requirements, architecture, ETL/ELT development, documentation, and operational support.
• Integrate and harmonize multi-modal R&D data across biomarker labs, translational platforms, clinical trials, real-world data/evidence (), genomics/other 'omics, and pre-clinical research systems to create trusted, reusable, AI-ready datasets .
• Co-develop an AI-ready data ecosystem in collaboration with Data Product Engineers, Data Scientists, Knowledge Graph Engineers, Enterprise Architecture, and IT-enabling advanced analytics, ML, and GenAI applications.
• Translate complex scientific, clinical, and operational needs into scalable engineering solutions , ensuring alignment with Oncology R&D priorities, enterprise data standards, and interoperability requirements.
• Design and optimize data pipelines for structured and unstructured data , leveraging Python, R, SQL, AWS services, and other relevant technologies to improve throughput, reliability, and maintainability.
• Implement robust data quality and reliability controls , including validation frameworks, automated monitoring, and KPI-driven measurement of data product performance, adoption, and business impact.
• Establish strong data governance foundations by maintaining data lineage, metadata, and versioning practices that support transparency, traceability, reproducibility, and compliance with internal and regulatory expectations. Embed FAIR data principles and compliance requirements into workflows

Required Qualifications:

• Bachelor's Degree in Computer Science, Engineering, Life Sciences, or other relevant field. Advanced degree preferred
• 5+ years of experience in data engineering, including data modeling, schema design and database architecture, preferably in the healthcare industry
• Demonstrated proficiency in data engineering tools such as Python, R and SQL for data