Amanjeet Singh developed a feature for the microsoft/fabric-samples repository focused on improving the portability and generalization of Jupyter notebooks. He engineered a metadata cleanup process using Python and JSON, systematically removing extraneous metadata fields and hardcoded identifiers from notebook files. This approach reduced metadata drift and simplified notebook structure, making assets more reusable across different environments. By addressing execution and language metadata, Amanjeet enhanced reproducibility and streamlined onboarding for new contributors. His work in data engineering and notebook management contributed to more maintainable and collaborative workflows, though the scope was limited to a single feature delivered over one month.