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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
Position Summary
Data Transformation Manager develops reproducible workflows that transform raw omics and imaging data into standardized, analysis- and AI-ready datasets. This role applies both computational and domain knowledge (e.g.,proteomics,transcriptomics) to ensure data quality, consistency, and interoperability across scientific studies.
Key Responsibilities
- Build and maintainNextflow/Snakemakepipelines for data ingestion, QC, and transformation of discovery datasets (e.g.,proteomics,RNA-seq,spatial omics,imaging)
- Convert raw assay outputs intoharmonized, AI-ready formatsthat can support data science, machine learning, and agentic exploration.
- Apply metadata and governance standards (FAIR, lineage, retention) to ensure data reproducibility and traceability.
- Collaborate with theSolution ArchitectandGovernance Teamsto align workflows with architectural standards and compliance frameworks.
- Document, test, and version-control workflows for scalability and reusability across studies.
Qualifications
- BS/MS/Ph.D inBioinformatics, Data Engineering, or Computer Science.
- 3 years of industry experience developing data pipelinesin research or analytics environments.
- Proficiency withNextflow,AWS, and scripting inPythonorBash.
- Working knowledge ofomics data types, includingproteomics,transcriptomics, and/orspatial omics.
- Familiarity withSnowflake,TileDB, and scientific data formats (FASTQ, HDF5, H5MU).
- Detail-oriented with strong commitment to data quality and reproducibility.
Strategic Impact
- Discovery datasets consistently delivered as standardized, AI-ready assets.
- Workflows accommodate multiple omics modalities and scale across projects.
- Improved data quality and transparency for downstream analytics and modeling.
Preferred Skills
- Advanced Analytics
- Business Intelligence (BI)
- Coaching
- Collaborating
- Critical Thinking
- Data Analysis
- Database Management
- Data Privacy Standards
- Data Reporting
- Data Savvy
- Data Science
- Data Visualization
- Econometric Models
- Process Improvements
- Technical Credibility
- Technologically Savvy
- Workflow Analysis
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