Worked on the iterative/datachain repository to enhance data ingestion reliability by addressing a critical issue with reading DataFrames containing MultiIndex columns. Applied data engineering expertise using Python and Pandas to develop a helper function that standardizes MultiIndex column names by joining tuple elements with underscores and converting them to lowercase. This approach ensured consistent and predictable column identifiers, reducing downstream data quality issues and improving pipeline stability. Expanded test coverage to validate the new functionality and prevent regressions. The work enabled analysts to trust pipeline outputs by minimizing errors related to inconsistent column naming in complex data processing scenarios.