Life Science Data Engineer

IFF•Madison, WI

2d•Onsite

About The Position

Are you passionate about transforming complex biological data into scalable solutions that drive scientific discovery? IFF is a global leader in flavors, fragrances, food ingredients and health & biosciences. We deliver sustainable innovations that elevate everyday products. Health & Biosciences: Channeling our passion for nature and bioscience into sustainable, life-enhancing technologies that power innovative solutions across healthcare, food, consumer and industrial markets. As a Life Science Data Engineer, you will play a key role in advancing digital transformation within microbiology and microbiome research and development. You will partner with scientists, bioinformaticians, and statisticians to design and scale data systems supporting experimental workflows, enabling data-driven discovery and real-world application of microbiome insights. The role is based in Madison, Wisconsin (on-site role). Be part of a collaborative, innovative, and solution-oriented team where together we can achieve meaningful impact. Your potential is our inspiration.

Requirements

Ph.D. in Data Engineering, Computational Biology, Data Science, or a related field with relevant experience; or M.S. with equivalent professional experience
Strong Structured Query Language (SQL) skills and experience with database systems such as SQL Server, PostgreSQL, or Oracle
Proficiency in Python, R, or Spark for data processing and analysis
Experience working with biological or experimental datasets with complex metadata structures
Familiarity with statistical or computational analysis of biological systems
Demonstrated ability to manage multiple projects and work independently in a dynamic environment
Strong communication and collaboration skills, with experience partnering effectively with scientific teams
Experience designing scalable data architectures and optimizing data workflows for downstream users

Nice To Haves

Knowledge of clinical data standards and models (e.g., Observational Medical Outcomes Partnership (OMOP), Clinical Data Interchange Standards Consortium (CDISC)) and healthcare coding systems
Experience working with microbiome or host–microbiome datasets, including translational or clinical research
Understanding of microbial physiology, fermentation processes, or multi-omics data integration

Responsibilities

Collaborate with scientific teams to design scalable data capture systems and user-friendly visualizations of experimental results
Design and implement database architectures, data models, and automated data pipelines across platforms (e.g., Amazon Web Services, Laboratory Information Management Systems, Benchling, and contract research organization systems)
Develop structured data models capturing microbial strain metadata, growth conditions, and experimental outputs
Partner with researchers to standardize experimental metadata, ontologies, and data structures to improve data quality, reproducibility, and traceability
Build and maintain data warehouses supporting probiotic growth, strain characterization, and clinical datasets
Develop and implement robust data quality and integrity checks across data ingestion workflows, including integration of externally generated clinical data
Build pipelines integrating multi-modal datasets (e.g., sequencing, metabolomics, in vitro assays, and clinical endpoints)
Partner cross-functionally to prototype and deploy digital solutions that enhance research and development efficiency and scalability