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Tech Stack
Tools & technologiesAWSOraclePostgresPythonSparkSQL
About the role
Key responsibilities & impact- 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
Requirements
What you’ll need- 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
Benefits
Comp & perks- Opportunity to work on impactful, real-world data and digital transformation projects
- Exposure to cutting-edge microbiome and probiotic research
- Collaborative environment with highly skilled scientists, engineers, and data experts
- Access to learning and development opportunities to grow technical and domain expertise
- Inclusive and purpose-driven culture focused on innovation and sustainability
ATS Keywords
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Hard Skills & Tools
Structured Query Language (SQL)PythonRSparkdatabase architecturesdata modelsautomated data pipelinesdata quality checksdata integrity checksdata processing
Soft Skills
communication skillscollaboration skillsproject managementindependent workdynamic environment adaptability
Certifications
Ph.D. in Data EngineeringPh.D. in Computational BiologyPh.D. in Data ScienceM.S. in related field