Data Transformation Manager

hace 1 semana

Cornellà de Llobregat Barcelona provincia, España Johnson & Johnson A tiempo completo

**Job Function**:
Data Analytics & Computational Sciences
**Job Sub Function**:
Data Science
**Job Category**:
Scientific/Technology
**All Job Posting Locations**:
Cornellà de Llobregat, Barcelona, Spain, Madrid, Spain

Johnson and Johnson Innovative Medicine (J&J IM), a pharmaceutical company of Johnson & Johnson is recruiting a Data Transformation Manager. This position has a primary location of Barcelona, Spain. The secondary location is Madrid. This is a hybrid role.

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

**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 maintain Nextflow/Snakemake pipelines for data ingestion, QC, and transformation of discovery datasets (e.g., proteomics, RNA-seq, spatial omics, imaging)
- Convert raw assay outputs into harmonized, AI-ready formats that can support data science, machine learning, and agentic exploration.
- Collaborate with the Solution Architect and Governance Teams to 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 in Bioinformatics, Data Engineering, or Computer Science.
- 3 years of industry experience developing data pipelines in research or analytics environments.
- Proficiency with Nextflow, AWS, and scripting in Python or Bash.
- Working knowledge of omics data types, including proteomics, transcriptomics, and/or spatial omics.
- Familiarity with Snowflake, 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.

JRDDS

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