To efficiently insert large datasets into a Postgres database, combining Spark's parallel processing with Python's COPY command can significantly enhance performance. By repartitioning the data and utilizing multiple writers, the author was able to insert 22 million records in under 14 minutes, leveraging Postgres's bulk-loading capabilities over traditional JDBC methods.