Developed the Sina Document Append Functionality for the LLNL/axom repository, enabling seamless in-place mutation of existing JSON and HDF5 documents by appending new records, updating fields, and extending curve sets. Leveraged C++ and Python to implement robust data serialization and file I/O, with a focus on maintaining data integrity through comprehensive validation and error handling. The solution reduces manual data manipulation and supports scalable data growth for downstream analytics. Emphasized clear traceability with detailed commit documentation and a focused pull request, ensuring maintainability and facilitating future enhancements within evolving data schemas and expanding curve-set requirements.