Design and optimize SQL and NoSQL data models and build ETL/ELT and next-generation data pipelines to support structured, semi-structured, and high-volume scientific data, analytics, and AI/ML workloads, including dataset preparation, feature engineering, and model integration into pipelines and applications. Design, develop, and maintain Python-based backend services, APIs, microservices, and data pipelines on AWS using FastAPI and supporting frameworks such as Flask or Django, including integrations with scientific systems such as Benchling, Signals, LIMS, ELN, CDS, and SDMS.