Biomedical Data Engineer 구성원 영입

D-169/16(수) 23:59 마감3685

경력

채용 유형

정규직

학력

학력무관

지역

경기도 판교

주요 업무

Design, develop, and maintain biomedical data pipelines integrating internal and external datasets Develop standardized, AI-ready multimodal biomedical datasets for AI and foundation model development Design and implement biomedical data models for structured and unstructured data Develop and optimize ETL workflows to support large-scale biomedical data processing Design biomedical ontologies, metadata standards, and knowledge graphs. Perform data harmonization, normalization, metadata management, and data quality validation across heterogeneous biomedical data sources Collaborate with AI scientists to prepare AI-ready datasets supporting machine learning and biomedical foundation model development Evaluate external biomedical databases and support long-term data acquisition strategies Contribute to the continuous improvement of the biomedical data platform, data governance practices, and engineering practices

자격 요건

Education : Bachelor's degree or higher Major : Bioinformatics, Computational Biology, Data Science, Data Engineering, Computer Science, or related fields Experience : 8-18 years of Experience designing and implementing biomedical or healthcare data platforms or large-scale data engineering solutions Strong proficiency in Python and SQL Hands-on Experience developing production-grade ETL pipelines and data integration workflows Experience with cloud-based data platforms (AWS) Experience working with structure and unstructured multimodal biomedical or healthcare data Strong understanding of data modeling, metadata management, and data quality assurance Excellent communication and collaboration skills in cross-functional research environments

우대 사항

Experience with genomics, transcriptomics, proteomics, imaging, or other multimodal biomedical datasets Experience with biomedical ontologies or knowledge graphs Experience with LLM-based information extraction Experience supporting foundation model development Experience in AI-driven drug discovery

채용 절차

서류전형 > 필기전형(SKCT) > 면접전형 > 채용검진/처우협의 > 최종합격 전형절차/일정은 상황에 따라 변동될 수 있으며, 전형 결과에 따라 추가 절차(인터뷰 등)가 진행될 수 있습니다. 채용 과정 중 필요 시, 지원자의 경력 및 평판 확인을 위해 레퍼런스 체크가 진행될 수 있습니다.

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