下面是一个使用Python代码示例的解决方案，该方案使用BigQuery的Python客户端库和Google Cloud Storage的Python客户端库来自动传输数据并覆盖表格：

from google.cloud import bigquery
from google.cloud import storage

# 设置Google Cloud项目和Bucket的名称
project_id = 'your-project-id'
bucket_name = 'your-bucket-name'

# 设置BigQuery目标表的名称和架构
table_id = 'your-dataset.your-table'
schema = [
    bigquery.SchemaField('column1', 'STRING'),
    bigquery.SchemaField('column2', 'INTEGER'),
    bigquery.SchemaField('column3', 'FLOAT'),
]

# 创建BigQuery客户端和存储客户端
bigquery_client = bigquery.Client(project=project_id)
storage_client = storage.Client(project=project_id)

# 从Google Cloud Storage下载数据文件
source_blob_name = 'path/to/data.csv'
destination_file_name = '/tmp/data.csv'
bucket = storage_client.get_bucket(bucket_name)
blob = bucket.blob(source_blob_name)
blob.download_to_filename(destination_file_name)

# 加载数据文件到BigQuery表中（覆盖表格）
job_config = bigquery.LoadJobConfig(schema=schema, write_disposition='WRITE_TRUNCATE')
with open(destination_file_name, 'rb') as source_file:
    job = bigquery_client.load_table_from_file(source_file, table_id, job_config=job_config)

job.result()  # 等待加载作业完成

# 删除临时数据文件
os.remove(destination_file_name)

print(f'Data loaded into table {table_id} successfully.')

请确保在运行此代码之前已安装所需的Python库（google-cloud-bigquery和google-cloud-storage）。