Senior Manager, Data Transformation - Neuroscience

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 Engineering

Job Category:

People Leader

All Job Posting Locations:

Cambridge, Massachusetts, United States of America, 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

Johnson & Johnson Innovative Medicine is recruiting for a Senior Manager, Data Transformation to join our J&J Research and Development Data, Data Science, and AI (DDSAI) team. This position will be located in either Raritan, NJ; Spring House, PA; Titusville, NJ; or Cambridge, MA, (no remote option), and may require some travel as needed.   

Position Summary:  

The Senior Manager, Data Transformation leads the development and operationalization of scalable, governed clinical and omics data products that transform raw data into interoperable, reusable, and AI-ready assets. The role owns the end-to-end data product lifecycle, including requirements, data modeling, processing, quality controls, metadata, lineage, versioning, access, and ongoing evolution based on user needs. 

This role requires both deep technical expertise and understanding of clinical and biological data, enabling cross-domain integration for discovery and translational research. 

Key Responsibilities:  

• Design and implement scalable data models for capturing AI-extracted Neuroscience clinical data from a diverse range of sources (e.g., the scientific literature) and data types (e.g., text, images). 

• Design and optimize Nextflow/Tower pipelines integrating AWS S3, Snowflake, and TileDB for large-scale data processing across proteomics, transcriptomics, metabolomics, and spatial omics from Neuroscience studies. 

• Establish reusable modules that standardize assay outputs into harmonized formats ready for data science and AI applications. 

• Collaborate with the Solution Architect, Vector Data Engineer, and Governance Teams to embed FAIR data principles and compliance requirements into workflows. 

• Lead pipeline optimization, code review, and development best practices. 

• Partner with AI/ML Core and Data Scientists to deliver AI-compatible, high-quality datasets for modeling and knowledge extraction. 

• Mentor junior engineers and drive workflow standardization and optimization across studies. 

Qualifications:

• MS/PhD in Bioinformatics, Data Engineering, or Computer Science. 

• 5+ years of experience developing data pipelines in a life sciences/drug discovery research or analytics environments.  Industry and/or Neuroscience experience are preferred.

• Hands-on experience with clinical data formats and models (e.g., CDISC SDTM/ADaM, FHIR, OMOP). 

• Hands-on experience with multi-omics workflows (proteomics, RNA-seq, metabolomics, or single-cell). 

• Hands-on experience with embedding or vector representation techniques for scientific data integration. 

• Proficiency with Nextflow, AWS, and scripting in Python or Bash. 

• Familiarity with Snowflake, TileDB, and scientific data formats. 

• Familiarity with clinical trial data and scientific literature is required.  Experience with an emphasis on Neuroscience (Neurodegeneration, Neuropsychiatry, or Ophthalmology) is preferred. 

• Detail-oriented, with strong commitment to data quality and reproducibility. 

Strategic Impact:  

• Improved interoperability between discovery, translational, and clinical data layers. 

• Clinical and multi-omics data delivered as standardized, AI-ready assets for analytics and modeling. 

• Reusable, compliant workflows accelerating scientific and AI insights across the enterprise. 

This position will be located in either Raritan, NJ; Spring House, PA; Titusville, NJ; or Cambridge, MA, (no remote option), and may require some travel as needed.   

Johnson & Johnson is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, age, national origin, disability, protected veteran status or other characteristics protected by federal, state or local law. We actively seek qualified candidates who are protected veterans and individuals with disabilities as defined under VEVRAA and Section 503 of the Rehabilitation Act.

If you are under 18 years of age, you (the candidate) may need to obtain the necessary working papers or other documentation required by state law to start the assignment, as well as get a parent’s consent for the background check.

Johnson & Johnson is committed to providing an interview process that is inclusive of our applicants’ needs. If you are an individual with a disability and would like to request an accommodation, external applicants please contact us via https://www.jnj.com/contact-us/careers , internal employees contact AskGS to be directed to your accommodation resource.

The anticipated base pay range for this position is $137,000 to $235,750. The Company maintains highly competitive, performance-based compensation programs. Under current guidelines, this position is eligible for an annual performance bonus in accordance with the terms of the applicable plan. The annual performance bonus is a cash bonus intended to provide an incentive to achieve annual targeted results by rewarding for individual and the corporation’s performance over a calendar/performance year. Bonuses are awarded at the Company’s discretion on an individual basis. Employees and/or eligible dependents may be eligible to participate in the following Company sponsored employee benefit programs: medical, dental, vision, life insurance, short- and long-term disability, business accident insurance, and group legal insurance.

Employees may be eligible to participate in the Company’s consolidated retirement plan (pension) and savings plan (401(k)).

Employees are eligible for the following time off benefits:
Vacation – up to 120 hours per calendar year
Sick time - up to 40 hours per calendar year
Holiday pay, including Floating Holidays – up to 13 days per calendar year of Work, Personal and Family Time - up to 40 hours per calendar year
Additional information can be found through the link below. https://www.careers.jnj.com/employee-benefits

The compensation and benefits information set forth in this posting applies to candidates hired in the United States. Candidates hired outside the United States will be eligible for compensation and benefits in accordance with their local market.

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Required Skills:

Preferred Skills:

Advanced Analytics, Agility Jumps, Budget Management, Compliance Management, Critical Thinking, Cross-Functional Collaboration, Data Engineering, Data Governance, Data Modeling, Data Privacy Standards, Data Science, Developing Others, Execution Focus, Hybrid Clouds, Inclusive Leadership, Leadership, Team Management, Technical Development, Technologically Savvy