### Apache Airflow Provider(s)

amazon

### Versions of Apache Airflow Providers

_No response_

### Apache Airflow version

2.3.3

### Operating System

MacOs/Linux

### Deployment

Docker-Compose

### Deployment details

_No response_

### What happened

sql_to_s3.py transfer has top level python code imports considered as Bad Practices:

https://github.com/apache/airflow/blob/be31214dcf14db39b7a5f422ca272cdc13e08268/airflow/providers/amazon/aws/transfers/sql_to_s3.py#L26

According to the [official docs](https://airflow.apache.org/docs/apache-airflow/2.3.3/best-practices.html#top-level-python-code):

```python
import numpy as np  # <-- THIS IS A VERY BAD IDEA! DON'T DO THAT!
```

All imports that are not related to DAG structure and creation should be moved to callable functions, such as the `execute` method.

This causes timeout errors while filling the `DagBag`:

```
  File "/opt/airflow/dags/mydag.py", line 6, in <module>
    from airflow.providers.amazon.aws.transfers.sql_to_s3 import SqlToS3Operator
  File "/home/airflow/.local/lib/python3.7/site-packages/airflow/providers/amazon/aws/transfers/sql_to_s3.py", line 25, in <module>
    import pandas as pd
  File "/home/airflow/.local/lib/python3.7/site-packages/pandas/__init__.py", line 50, in <module>
    from pandas.core.api import (
  File "/home/airflow/.local/lib/python3.7/site-packages/pandas/core/api.py", line 48, in <module>
    from pandas.core.groupby import (
  File "/home/airflow/.local/lib/python3.7/site-packages/pandas/core/groupby/__init__.py", line 1, in <module>
    from pandas.core.groupby.generic import (
  File "/home/airflow/.local/lib/python3.7/site-packages/pandas/core/groupby/generic.py", line 73, in <module>
    from pandas.core.frame import DataFrame
  File "/home/airflow/.local/lib/python3.7/site-packages/pandas/core/frame.py", line 193, in <module>
    from pandas.core.series import Series
  File "/home/airflow/.local/lib/python3.7/site-packages/pandas/core/series.py", line 141, in <module>
    import pandas.plotting
  File "<frozen importlib._bootstrap>", line 983, in _find_and_load
  File "<frozen importlib._bootstrap>", line 967, in _find_and_load_unlocked
  File "<frozen importlib._bootstrap>", line 677, in _load_unlocked
  File "<frozen importlib._bootstrap_external>", line 724, in exec_module
  File "<frozen importlib._bootstrap_external>", line 859, in get_code
  File "<frozen importlib._bootstrap_external>", line 917, in get_data
  File "/home/airflow/.local/lib/python3.7/site-packages/airflow/utils/timeout.py", line 68, in handle_timeout
    raise AirflowTaskTimeout(self.error_message)
airflow.exceptions.AirflowTaskTimeout: DagBag import timeout for /opt/airflow/dags/mydag.py after 30.0s.
Please take a look at these docs to improve your DAG import time:
* https://airflow.apache.org/docs/apache-airflow/2.3.3/best-practices.html#top-level-python-code
* https://airflow.apache.org/docs/apache-airflow/2.3.3/best-practices.html#reducing-dag-complexity, PID: 7
```

### What you think should happen instead

_No response_

### How to reproduce

_No response_

### Anything else

_No response_

### Are you willing to submit PR?

- [X] Yes I am willing to submit a PR!

### Code of Conduct

- [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

"""
    Saves data from a specific SQL query into a file in S3.
    .. seealso::
        For more information on how to use this operator, take a look at the guide:
        :ref:`howto/operator:SqlToS3Operator`
    :param query: the sql query to be executed. If you want to execute a file, place the absolute path of it,
        ending with .sql extension. (templated)
    :param s3_bucket: bucket where the data will be stored. (templated)
    :param s3_key: desired key for the file. It includes the name of the file. (templated)
    :param replace: whether or not to replace the file in S3 if it previously existed
    :param sql_conn_id: reference to a specific database.
    :param parameters: (optional) the parameters to render the SQL query with.
    :param aws_conn_id: reference to a specific S3 connection
    :param verify: Whether or not to verify SSL certificates for S3 connection.
        By default SSL certificates are verified.
        You can provide the following values:
        - ``False``: do not validate SSL certificates. SSL will still be used
                (unless use_ssl is False), but SSL certificates will not be verified.
        - ``path/to/cert/bundle.pem``: A filename of the CA cert bundle to uses.
                You can specify this argument if you want to use a different
                CA cert bundle than the one used by botocore.
    :param file_format: the destination file format, only string 'csv', 'json' or 'parquet' is accepted.
    :param pd_kwargs: arguments to include in DataFrame ``.to_parquet()``, ``.to_json()`` or ``.to_csv()``.
    """
    template_fields: Sequence[str] = (
        "s3_bucket",
        "s3_key",
        "query",
        "sql_conn_id",